Enhanced control for compression and decompression of sampled signals

Control of signal compression is coordinated by selectively modifying control parameters affecting the bit rate, sample rate, dynamic range and compression operations. Selected control parameters are modified according to a control function. The control function can include a ratio parameter that indicates the relative or proportional amounts of change to the control parameters. Alternatively, the control function can be represented in a lookup table with values for the selected control parameters related by the control function. The input signal samples can be resampled according to a sample rate control parameter. The dynamic range of signal samples can be selectively adjusted according to a dynamic range control parameter to form modified signal samples. The resampling and dynamic range adjustment can be applied in any order. The modified signal samples are encoded according to a compression control parameter to form compressed samples. The encoder can apply lossless or lossy encoding.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to compression and decompression of sampled signals, particularly to applying coordinated control of two or more control parameters for the compression operations.

2. Description of Related Art

In a signal processing system, it may be necessary to apply lossy compression to the signal samples in order to accommodate a system constraint. Constraints, including limited storage capacity or limited data transfer bandwidth, can prevent storage and/or transfer of the entire bandwidth and dynamic range of the signal samples. Ideally, lossless compression can be applied before data storage or data transfer followed by decompression before additional signal processing. In lossless compression, the decompressed signal samples are identical to the original signal samples. If lossless compression does not give adequate reductions in the bit rate of the compressed signal, then lossy compression may be necessary to provide sufficient reduction of the bit rate. In lossy compression, the decompressed, or reconstructed, signal samples are similar, but not identical to, the original signal samples, creating distortion in the characteristics of the reconstructed signal. Lossy compression creates a tradeoff between the bit rate of the compressed signal samples and the distortion in the reconstructed signal samples. The signal characteristics that may be distorted include, but are not limited to, amplitude, frequency, bandwidth and signal-to-noise ratio (SNR). The availability of computing resources to implement the compression algorithm may also be a system constraint in some instances. In this situation, it is desirable to minimize the computing resources required by either lossless or lossy compression algorithms.

In this discussion, “dynamic range” refers to the range of magnitudes available to the signal samples. Dynamic range can be expressed using a linear scale or a logarithmic scale using units of decibels (dB). The relationship of the logarithmic scale and the linear scale follow the well known equation:
dB=20*log2(magnitude),
where magnitude is in arbitrary linear units, such as voltage. The present invention focuses on signal samples whose dynamic range is limited by the number of bits per sample. The “6 dB per bit” rule, known to those skilled in the art, indicates that each bit level provides 6 dB of dynamic range for signal samples. For example, eight bits per sample accommodates 48 dB of dynamic range. Initially an analog to digital converter (ADC) converts an original analog signal to digital signal samples. So an initial dynamic range of the signal samples depends on the bit width available from the ADC. A similar relationship exists for the dynamic range of digital samples that are converted from the digital to the analog domain by a digital to analog converter (DAC).

In this discussion, “real time” means a rate that is at least as fast as the sample rate of a digital signal. The term “real time” can be used to describe rates for processing, transfer and storage of the digital signal. The sample rate is the rate at which the ADC forms samples of the digital signal during conversion of an analog signal. When converting a digital signal to an analog signal, the sample rate is the rate at which the DAC forms the analog signal from the samples of the digital signal. The bit rate of an uncompressed sampled, or digital, signal is the number of bits per sample multiplied by the sample rate. The compression ratio is the ratio of the bit rate of the original signal samples to the bit rate of the compressed samples.

Current methods of signal data compression generally identify redundancies in the signal data and reduce the redundancies in order to compress the data. For instance, in transform encoding, an orthogonal transform such as a Discrete Cosine Transform (DCT) is applied to the signal samples to form transform coefficients. The transform coefficients are then encoded in order to compress the data. In this example, the redundancy is represented by the various frequencies of the basis functions of the transform and the corresponding transform coefficients. Compression is achieved by eliminating selected transform coefficients with low values, truncating in the frequency domain by eliminating coefficients above a certain cutoff frequency, reducing the bit width of the transform coefficients and/or quantizing the coefficients with larger step sizes requiring fewer bits per coefficient. After inverse transformation, the reconstructed signal samples are rarely identical to the original signal samples. If there was a truncation in the frequency domain, Gibbs' phenomenon (ripple) can cause unwanted oscillations in the time domain reconstructed signal samples. Amplitude distortion may also result from quantization of the transform coefficients. In the time domain, lossy compression can be accomplished by removing least significant bits (LSBs) or applying coarser quantization so that there are fewer quantization levels per sample resulting in fewer bits per sample. Quantization of time domain samples or frequency domain transform coefficients both cause distortion in the amplitude of the reconstructed signal samples compared with the original signal samples. In addition, applying coarser quantization will also increase quantization noise. Time domain compression methods also identify redundancies in the signal. For example, compression methods based on the well known Huffman encoding calculate a histogram of symbol frequencies. The symbols can correspond to original signal samples or differences between signal samples. Symbols with higher frequencies of occurrence are assigned shorter codes while those with lower frequencies of occurrence are assigned longer codes. Techniques such as prefix coding can be used to ensure that the stream of variable-length codes can be accurately decoded. A sequence of codes corresponding to the sequence of values is bit-packed to form a compressed sequence. A lossy compression method in the time domain includes calculating the differences between samples and coarsely quantizing the differences. When the differences are added back in during decompression, the resulting reconstructed signal samples will have amplitude distortion and increased quantization noise resulting in a lower SNR.

Those skilled in the art recognize that distortion is a result of lossy compression. In information theory, the familiar tradeoff between the compressed signal's bit rate and distortion in the reconstructed, or decompressed, signal is often represented by a rate-distortion curve. It would be advantageous to control which signal characteristics are affected by the distortion introduced by lossy compression. In one application, the bandwidth of the signal samples may be a more critical characteristic to preserve while in another application, the dynamic range may be more critical to preserve by minimizing amplitude distortion. In yet another application, a balance between distortion in the dynamic range and bandwidth is advantageous. For example, in spread spectrum signals, such as code division multiple access (CDMA), a narrowband signal is modulated by a spreading sequence such that the signal spectrum is distributed across a wide band of frequencies. For this example, it would be more important to preserve the bandwidth of the spread signal since all of its frequency components are needed for despreading. After despreading the signal back to its original narrowband form, it may be more important to preserve the signal amplitude.

Previous methods for controlling signal compression provide for control of various parameters. The most common control parameter is the bit rate of the compressed signal or the corresponding compression ratio. In the commonly owned U.S. Pat. No. 7,009,533 B1 (the '533 patent), entitled “Adaptive Compression and Decompression of Bandlimited Signals”, dated Mar. 7, 2006, the present inventor describes algorithms for compression and decompression of certain bandlimited signals including control of compression. The '533 patent discloses controlling preprocessor and compressor operations in feedforward and feedback configurations and in response to user input. In the commonly owned U.S. Pat. No. 5,839,100 (the '100 patent), entitled “Lossless and Loss-Limited Compression of Sampled Data Signals”, dated Nov. 17, 1998, the present inventor describes efficient algorithms for compression of sampled data signals without loss or with a controlled amount of loss that affects the signal's dynamic range.

The previous methods do not provide coordinated control over the relative distortions in signal characteristics. Coordinated control allows control of the tradeoffs among the relative signal distortions during signal compression. Improved control will enhance the performance and accuracy of the signal processing system. The present invention fulfills these needs and provides further related advantages as described in the following summary.

SUMMARY OF THE INVENTION

An object of the invention is to provide coordinated control of signal compression by determining control parameters affecting the sample rate, dynamic range and compression operations. Selected control parameters are determined according to a control function. The input signal samples are resampled according to a sample rate control parameter. The sample rate control parameter can also indicate no resampling. Resampling may change the bandwidth of the resampled signal samples compared with the input signal samples. The dynamic range of resampled signal samples is reduced according to a dynamic range control parameter to form modified signal samples. The dynamic range control parameter can also indicate that the resampled signal samples will not be adjusted. The resampling and dynamic range adjustment can be applied in any order. The modified signal samples are encoded to form compressed samples. The encoder can apply lossless or lossy encoding.

The control function can include a ratio parameter that indicates the relative or proportional amounts of change to the control parameters. When the selected control parameters are the sample rate control parameter and the dynamic range control parameter, the ratio parameter is used to determine the relative amounts of change for the resampler and dynamic range adjuster. The control function characteristics can also be represented by a lookup table that contains values corresponding to two or more selected control parameters related by the control function. The user can modify the control function characteristics or the ratio parameter.

A graphical user interface (GUI) for the selection of control function characteristics includes a scale with a pointer. One end of the scale represents a minimum change to a particular control parameter and the other end represents a minimum change to a different control parameter. The location of the pointer on the scale indicates a value for a control function characteristic or a ratio parameter. When the scale represents the sample rate control parameter and the dynamic range control parameter, the pointer location indicates a value for the ratio parameter or other control function characteristic that indicates the relative changes in these two control parameters. The scale allows the user to select and coordinate the relative amounts of change to be applied to the selected control parameters.

Another object of the invention is a resampler that provides additional compression in a lossless mode or a lossy mode. The resampler operates to downsample the input signal samples at a reduced sample rate. The downsampled signal samples are then upsampled to the original sample rate. The upsampled signal samples are subtracted from the original signal samples to form error, or residual, samples. The downsampled signal samples and error samples are encoded to form compressed samples. Alternatively, the downsampled signal samples and error samples can be attenuated or quantized to provide additional compression.

Another object of the invention is decompression of the compressed samples. The decompressor decodes the compressed samples to provide decoded signal samples and decoded error samples. The decoded signal samples are upsampled to the original sample rate. The decoded error samples are added to the upsampled signal samples to form the reconstructed signal samples at the original sample rate. The error signal can optionally be omitted from the compressed stream.

DETAILED DESCRIPTION

FIG. 1is a block diagram of a signal compressor previously described in the '533 patent. The preprocessor110performs various selectable operations on the input signal samples100to produce preprocessed signal samples105with lowpass or other desired characteristics for the compression operations of the compressor120. Some of the preprocessor operations will be described below with respect toFIG. 9. The preprocessor110can also measure various characteristics of the input signal samples100, such as center frequency, noise floor and bandwidth. The compressor120applies selected operations that compress the preprocessed signal samples105including computing first or higher order differences, or derivatives, of the preprocessed signal samples105, approximating certain signal samples through mathematical operations on other preprocessed signal samples105, encoding (such as Huffman encoding) and bit-packing. The control module130produces control parameters for operations of the preprocessor110and the compressor120. The control module130receives user input143, measurements115of signal characteristics from the preprocessor110for feedforward control and measurements123of compression performance from the compressor120for feedback control. The user140can select control of signal quality, compression ratio or output bit rate in the compressed signal125. The control module130calculates control parameters133for the preprocessor110and control parameters135for the compressor based on the measurements115and123and user input143.

FIG. 2is a block diagram of a signal compressor in accordance with a preferred embodiment of the present invention. An optional preprocessor210performs operations such as filtering, downconversion and other operations to prepare the input signal samples100for compression. The purpose of the preprocessor210is to produce preprocessed signal samples211with lowpass or other characteristics that can be effectively compressed by the signal compression processor220. The preprocessor210produces one or more lowpass signal streams from an input signal by selectively reordering and selectively inverting signal samples100. The preprocessor210receives control parameters212from the controller input processor270. The operation of the preprocessor210will be described below with respect toFIG. 9. The signal compression processor220applies signal processing and compression operations described below with respect toFIG. 3to form compressed samples225. The controller240provides coordinated control parameters261aand261bfor coordinated control of two different operators of the signal compression processor220. The controller240includes a controller input processor270and a control function processor260. The controller input processor270receives input281via a user interface280from a user140. Processing modules for signal parameter measurement230and compressed data measurement250also provide inputs231and251, respectively, to controller input processor270. The signal parameter measurement module230is optional when the signal parameters231are known parameters. The compressed data measurement module250measures parameters of the compressed samples225to form feedback parameters for the controller240. The user140selects feedback control of output bit rate or signal quality parameters. When feedback control of bit rate is desired, the measured parameter can be output bit rate of the compressed samples or the compression ratio. When feedback control of signal quality is desired, the feedback parameter is based on a signal quality parameter, such as signal to noise ratio, noise floor or bit error rate of decompressed, or reconstructed, signal samples corresponding to the compressed samples. For feedback control of the signal quality parameter, the compressed data measurement module250decompresses the compressed samples225and measures the signal quality parameter of the decompressed, or reconstructed, signal samples. The controller260applies any operations that convert the inputs281,231and251into control parameters261a,261band271for the signal compression processor220. Depending upon the implementation, controller260may examine all inputs or a subset of inputs, and may generate all control parameters or a subset of control parameters. In a preferred embodiment, the control function processor260applies a control function to form coordinated control parameters261aand261bbased on the parameters273received from the controller input processor270. The control function provides coordinated control of distortions in selected signal characteristics, as described below with respect toFIG. 5. Controller input processor270can also perform calculations to produce an independent control parameter271. The user interface280can include a graphical user interface described below with respect toFIG. 6.

FIG. 3is a block diagram of an embodiment of the signal compression processor220. The resampler310resamples the signal samples100to form resampled signal samples311. Alternatively, if preprocessor210produces one or more signal sample streams, the resampler resamples each stream of preprocessed signal samples211. The resampler310can downsample or upsample the signal samples100in accordance with a sample rate control parameter312. The resampler310is described in greater detail below with respect toFIG. 4. Depending on the sample rate control parameter312, the resampled signal samples311can have a reduced sample rate resulting in a lower bit rate compared to the bit rate of the input signal samples100. The dynamic range adjuster320modifies the amplitudes of the resampled signal samples311in accordance with dynamic range control parameter322to produce modified signal samples321. Depending on the dynamic range control parameter322, the modified signal samples321can have a reduced dynamic range of amplitudes. The reduced amplitudes can be represented by fewer bits per sample resulting in a reduced bit rate for the modified signal samples321compared with that of the input signal samples100. If the user selects the sample rate control parameter312and the dynamic range control parameter322for coordinated control, the control function processor260provides corresponding coordinated control parameters,261aand261b, respectively. If the user selects independent control, the controller input processor270provides independent control parameters271for the sample rate control parameter312and the dynamic range control parameter322. The order of the operations of dynamic range adjuster320and resampler310can be reversed, i.e. the dynamic range adjuster320can perform its function on signal samples100or211before the resampler310is applied. The signal processing operations of resampling and dynamic range adjustment provide some compression of the signal samples100or211.

The encoder330applies lossless or lossy compression in accordance with compression control parameter332. The encoder330can apply bit-packing logic directly to the modified signal samples321. To provide additional compression prior to bit-packing, encoder330can calculate first or higher order derivatives, or differences, of the modified signal samples321followed by encoding the derivatives using bit-packing logic. Alternatives for bit-packing logic include Huffman encoding, arithmetic encoding, block exponent encoding, Rice encoding, or other lossless encoding. The compression control parameter332can be provided to the encoder by the controller input processor270as independent control parameter271. Alternatively, the control function processor260can provide coordinated control of the compression control parameter332in coordination with the sample rate control parameter312or the dynamic range control parameter322using coordinated control parameters261aand261b.

The preferred embodiment for the dynamic range adjuster320is a programmable multiplier that applies a factor in accordance with the dynamic range control parameter322. To reduce the dynamic range, or attenuate, the signal samples, the value of the factor is less than one. The signal samples with reduced dynamic range are represented using fewer bits. In another embodiment, the dynamic range adjuster is a requantizer that maps the amplitudes of signal samples100,211or311, depending on which previous operations are selected, to representations having fewer bits per sample. In another embodiment, the dynamic range adjuster320uses a shift register that right shifts sample values to reduce a number of least significant bits (LSBs) in accordance with the dynamic range control parameter322. The dynamic range adjuster320can remove LSBs based on the noise floor of the signal samples100. If the noise floor is not known, the signal parameter measurement module230measures the noise floor in the signal samples100. The controller input processor270calculates the dynamic range control parameter322based on the noise floor estimate to remove bits that are primarily noise. This approach is described in greater detail in the '533 patent with respect toFIG. 6andFIGS. 18-26.

The resampler310can include a polyphase sampling filter or a Farrow filter, both well known to those skilled in the art. The Farrow filter is preferred because it requires fewer computations, resulting in ten to thirty percent fewer gates for an implementation compared to a polyphase filter. The Farrow filter is described by Cecil W. Farrow in U.S. Pat. No. 4,866,647 and in Chapter 7 of the book entitled “Multirate Signal Processing for Communication Systems” by fredric j harris, published by Prentice Hall PTR. The Farrow filter is effective for baseband or lowpass signals. If the input signal samples100are not at baseband, the preprocessor210can apply operations to produce lowpass or baseband signal samples. Alternatives include downconverting the signal samples100to baseband, lowpass filtering the signal samples100or separating the signal samples100into one or more streams of lowpass signal samples as described with respect toFIG. 9. The Farrow filter would then be applied to preprocessor output signal samples211. Resampling using a Farrow filter can provide fractional changes in sample rate, whereas resampling using a polyphase sampling filter typically provides rational changes in sample rate according to the ratio m/n, where m and n are integers. The Farrow filter can also provide non-uniform sampling where the sample intervals between consecutive samples can vary in length. For non-uniform sampling, the resulting sample rate is an average sample rate for the resampled signal samples.

A preferred embodiment for decompression restores the original sample rate to the decompressed signal samples. Downsampled signal samples can be upsampled back to the original sample rate using a Farrow filter or a polyphase filter. A Farrow filter is preferred, as described below with respect toFIG. 4. In general, because resampling operations are most often implemented using arithmetic elements (adders, multipliers, and the like) having limited bit widths, upsampling the downsampled signal samples back to the original sample rate produces upsampled signal samples that differ slightly from the original signal samples. In some applications, it is desirable to remove the resampling error (also called the residual) in the upsampled signal samples. Additional operations in the signal compression processor220can measure and encode the resampling error for use by the decompressor.

FIG. 4is a block diagram of an alternative embodiment for the resampler310that includes determining the resampling error. This embodiment for the resampler310can be configured to provide lossless or lossy compression. The input samples400are the signal samples100, the preprocessor output samples211or modified signal samples321produced by dynamic range adjuster320prior to resampling, depending on which previous operations are selected. The downsampler420applies a Farrow or polyphase filter to downsample the input samples400in accordance with the sample rate control parameter312to produce the resampled, or downsampled, signal samples311. The upsampler430applies a Farrow or polyphase filter to upsample the downsampled signal samples311at the original sample rate to form upsampled signal samples431. The upsampled signal samples have samples at the same points in time as the original input samples400for the downsampler420, however the amplitudes of the upsampled signal samples431may not be identical to those of the corresponding input samples400. The delay buffer440delays the input samples400to provide temporal alignment with the upsampled signal samples431, compensating for processing delays in the downsampler420and the upsampler430. The subtractor450subtracts each upsampled signal sample431from its corresponding time-aligned signal sample441to form a corresponding error sample451. The error samples451are encoded by the encoder330or scaled by the dynamic range adjuster320prior to encoding. The downsampled signal samples311are also encoded by the encoder330or scaled by the dynamic range adjuster320prior to encoding. The encoded error samples and the encoded downsampled signal samples are included in the compressed samples225. For a lossless compression mode, the encoder330applies lossless encoding to both the error samples451and the downsampled signal samples311. For a lossy compression mode, dynamic range adjuster320and/or the encoder330can apply lossy operations to the downsampled signal samples311and/or the error samples451. Lossy compression also results from not calculating or not encoding the error samples451.

The control function processor260provides coordination of at least two control parameters selected by the user. Coordination of the selected control parameters allows some control of the types of distortion that result from the corresponding compression operations. The control function processor260applies a control function to determine changes in the selected control parameters. The characteristics of the control function can be selected by the user. Characteristics of the control function can be represented by a ratio parameter, a lookup table representing values of the control function characteristics or a combination of both.

In a preferred embodiment, the control function processor260includes a ratio parameter. The ratio parameter relates the change to a first control parameter to the change in a second control parameter. The change for each control parameter is calculated by multiplying a change factor by a corresponding step size. Changes in control parameters CP1and CP2are determined as follows:
CP1(new)=CP1(old)+F1*Step1  (1)
CP2(new)=CP2(old)+F2*Step 2  (2)
Ratio Parameter=F2:F1=F2/F1  (3)
where Step1is the step size for the first control parameter CP1, Step2is the step size for the second control parameter CP2, F1is the change factor for CP1and F2is the change factor for CP2. The ratio parameter is the ratio of the factors F2and F1and represents the number of steps of change in CP2for each step of change in CP1. For example, for a ratio parameter of 1, or 1:1, one step of change is applied to CP1and one step of change is applied to CP2. For a ratio parameter of 2, or 2:1, two steps of change are applied to CP2and one step of change is applied to CP1. The units of measure for the control parameters CP1and CP2are likely to be different because they relate to different characteristics of the signal, such as bandwidth (normally measured in Hz) and dynamic range (normally measured in dB). The step sizes are set by the user for the corresponding control parameter. For example, CP1can be the sample rate control parameter, measured in units of Hz, and CP2can the dynamic range control parameter, measured in units of dB. The user can set corresponding step sizes that are appropriate for the signal being compressed. The user also sets the ratio parameter which allows control of relative changes in the control parameters. Through the ratio parameter, the user can control the degree of change in one signal characteristic relative to another signal characteristic.

The first control function530corresponds to a ratio parameter that is less than one, meaning that for every step of change in dynamic range, there are more than one steps of change in sample rate. The control function530is linear with a slope equal to the ratio parameter until it reaches the Nyquist frequency. At this point, the sample rate control parameter312would be fixed at the Nyquist frequency so that there are no further reductions in sample rate by the resampler310. Any further reduction in bit rate would occur by reducing dynamic range further by the dynamic range adjuster320and/or increasing compression by the encoder330. The second control function540corresponds to a ratio parameter that is greater than one, meaning that for every step of change in sample rate, there are more than one steps of change in dynamic range. The second control function540is linear until it reaches the minimum dynamic range. At this point, there are no further reductions in dynamic range by dynamic range adjuster320. Any further reduction in bit rate would occur by reducing the sample rate by resampler310and/or increasing compression by the encoder330. A pair of change factors (F1, F2) corresponds to a point along the control function graph. For example, the original sample rate and dynamic range correspond to F10=0 and F20=0, respectively, and the point560. Change factors F11and F21correspond to sample rate control parameter CP11and dynamic range control parameter CP21, respectively, and point570along the second control function540. In this example, change factors F11and F21are negative.

The control function can be a continuous function defined by the user. The control functions530and540are piecewise linear. Smooth control functions such as the third control function535and the fourth control function545can also be defined. These can be represented in a lookup table in memory that includes a column of entries for each control parameter. The ratio parameter is not constant for control functions535and545. For a non-constant ratio parameter, F1and F2are related by a nonlinear function as follows,
F2=fRP(F1)  (5a)
where the function fRPrepresents the changing ratio parameter. The control function processor260can represent the control function based on a changing ratio parameter in a lookup table in memory that includes entries for the ratio parameter, F1and F2.

The example ofFIG. 5ashows control functions that coordinate changes in sample rate and dynamic range. However, coordinated control can be applied to other signal characteristics that are affected by compression operations. For example, let the compression control parameter indicate the desired bit rate or compression ratio of the compressed data at encoder output. The compression control parameter can be based on any user-specified figure of merit that is a function of the output bit rate, including output SNR, bit error rate (BER), error vector magnitude (EVM), rise time, fall time or jitter specification. A control function can be defined to provide coordinated control to the compression control parameter and the sample rate control parameter or the compression control parameter and the dynamic range control parameter.

In an alternative embodiment, the control function processor260can modify more than two control parameters in accordance with a multidimensional control function to achieve the desired types of distortion. The multidimensional control function can be defined by entries in one or more lookup tables. For example, a control function for three control parameters can be represented by a lookup table with a column of entries for each of the control parameters. Alternatively, the control function can be represented by a mathematical relationship. For example, for three control parameters, ratios A:B:C indicating relative changes among the control parameters can be defined by the user.

In another alternative embodiment, the control function is represented by a user-defined functional relationship between the selected control parameters. The control function can be represented mathematically as a predefined function fCPwhere,
CP2=fCP(CP1)  (5b)

The control function fCPfor CP1and CP2can be represented by a mathematical formula or a lookup table in memory.FIG. 5bgives two examples of lookup tables that define relationships between control parameters CP1and CP2that correspond to the control function. Each lookup table580aorbincludes three columns: an index or address column581aorb, a column of entries584aorbfor the first selected control parameter CP1, and column of entries586aorb for the second selected control parameter CP2. The lookup tables can contain any number of rows depending on how the user defines the control function. For example, lookup table580ahas 256 rows and lookup table580bhas 512 entries. Current values of CP1and CP2are specified by a row pointer or address582aorb. Row pointer582aorbcan indicate a different row in response to the difference between the user-specified goal and a measured performance parameter towards this goal, further described below. The values in columns584aorband586aorbcan represent an arbitrary shape, such as those of smooth curves535and545inFIG. 5a. For the first lookup table580a, the first three entries of column586acontain the same values (1.0), which allow users to specify a limiting value such as the flat horizontal region of curve540inFIG. 5a. In the second table580b, the first four example entries in column584b{1.00, 1.04, 1.00, 1.03} are not monotonic, i.e. they are not continuously decreasing or increasing across the range. These examples demonstrate that any user-defined control function can be represented in the column entries of a lookup table. In each of these examples, the lookup tables580aand580bdefine a relationship between the sample rate control parameter, CP1, and dynamic range control parameter, CP2. The resampler310resamples the input signal samples100or211with a reduced sample rate equal to the input sample rate divided by CP1. The dynamic range control parameter, CP2, represents an attenuation factor such that the dynamic range adjuster320multiplies the signal samples311by CP2. Note that these alternative representations for CP1and CP2are different than those described with respect to equations (1), (2) and (3). As a numerical example, row pointer582aa selects row 3 of lookup table580ain which the value of CP1is 1.04 and the value of CP2is 1.00. The resampler310will resample the signal samples with the sample rate divided by 1.04. The dynamic range adjuster320will simply pass the samples with no change in amplitude since CP2 equals 1.0. The lookup table method can include more than two columns of control parameters for multidimensional control functions.

The user configures the coordinated control by selecting the control parameters, the control function, the ratio parameter and other processing parameters via the user interface280. In a preferred embodiment, the user interface280includes a GUI with graphical features that are relevant for coordinated control. The user selects the control function and/or the ratio parameter that coordinate the control of the selected control parameters. For ratio parameter selection, the GUI includes a scale that represents a range of ratio parameters available for the selected control parameters.FIG. 6gives an example of a scale for the GUI. The scale600is represented by a line segment having endpoints610and620. The endpoint610represents a ratio parameter that produces minimum change in the first control parameter CP1. The endpoint620represents a ratio parameter that produces a minimum change in control parameter CP2. The ratio parameter is represented as the ratio of change factors F2:F1, as indicated in equation (3). The ratio parameter is at the minimum of its range at the endpoint620corresponding to a minimum change in CP2. At the endpoint620, the change factor F2for control parameter CP2has its lowest value and the change factor F1for control parameter CP1has its highest value. The ratio parameter is at the maximum of its range at endpoint610corresponding to a minimum change in CP1. At the endpoint610, the change factor F1for control parameter CP1has its lowest value and the change factor F2for control parameter CP2has its highest value. The X location630on the scale indicates the ratio parameter value of 1:1. The X location630is not necessarily the midpoint of scale600. For the ratio of 1:1, a step of change in CP2occurs for every step of change in CP1. For example, if there are four steps of change in CP1, there are four steps of change in CP2. The pointer640responds to user input to select a particular ratio parameter corresponding to the point650on the scale600.

The scale601provides a numerical example. The endpoint611corresponding to a minimum change in the control parameter CP1represents a ratio parameter of 4:1. The endpoint621corresponding to a minimum change in the control parameter CP2represents a ratio parameter of 1:4. The X location631indicates the ratio parameter 1:1. For this example, the minimum ratio parameter is the inverse of the maximum ratio parameter. This is not a requirement. However, when this inverse relationship exists, the 1:1 ratio parameter is located at the midpoint of the scale. When the minimum ratio parameter and maximum ratio parameter are not inverses, the 1:1 ratio may not be located at the midpoint of the scale. The pointer641selects the ratio parameter corresponding to the point651. The change factors F1and F2can be whole or fractional numbers.

For nonlinear control functions, such as those represented inFIG. 5by curves535and545, a ratio parameter can be selected for the approximately linear region of the control function. During operation, as the control parameters CP1and CP2approach the nonlinear region of the control function, the control function processor260modifies the ratio parameter, F1and F2in accordance with the control function. The control function can include thresholds values for CP1and CP2that indicate the beginning of the nonlinear region. In the nonlinear region, the control function processor260can use a lookup table to determine the ratio parameter and the change factors F1and F2.

Referring toFIG. 2, an embodiment of the control function processor260performs the calculations to adjust the selected control parameters CP1(261a) and CP2(261b) in accordance with the ratio parameter, the corresponding change factors F1and F2and the corresponding step sizes Step1and Step2. The controller input processor270can receive inputs from the user interface280, the signal parameter measurement module230and the compressed data measurement module250. In response to the inputs231,281and251, the controller input processor270determines whether the selected control parameters CP1and CP2should be changed. For example to produce a desired bit rate, the controller input processor270provides the desired bit rate to the control function processor260. The control function processor260can calculate the changes in CP1and CP2in accordance with the ratio parameter that will produce approximately the desired bit rate. Alternatively, the control function processor260can apply a positive or negative step change in accordance with equations (1) and (2), where the signs of F1and F2are positive or negative depending on the polarity of the desired change.

For example, let CP1correspond to the sample rate control parameter312and CP2correspond to the dynamic range control parameter322. The control function processor260adjusts the control parameters CP1and CP2such that the resampler310and dynamic range adjuster320produce a change from the current bit rate to the desired bit rate for the modified signal samples321. Referring to equation (1), changing CPI by the amount F1*Step1changes the sample rate by x samples/second. Referring to equation (2), changing CP2by F2*Step2changes the number of bits to represent each sample by y bits/sample. The change in bit rate is related to the changes in the control parameters by the product of x and y as follows:
bit rate change=zbits/second=xsamples/second*ybits/sample  (6)
The control function processor260can determine the number of steps N required to reach the desired bit rate change as follows:
N=desired bit rate change/z(7)
The number of steps N can be a whole or fractional number. The change factors F1and F2can be multiplied by N so that CP1and CP2are updated as follows:
CP1(new)=CP1(old)+N*F1*Step1  (8)
CP2(new)=CP2(old)+N*F2*Step 2  (9)
The ratio parameter is the same, since
Ratio Parameter=F2/F1=N*F2/N*F1  (10)
For this example, the bit rate change was calculated exactly using equation (6). In one alternative, approximations of the bit rate change and the number of steps N can be used to update the control parameters CP1and CP2. In another alternative, the control function processor260can apply a positive or negative step change in accordance with equations (1) and (2), where the signs of F1and F2correspond to the polarity of the desired bit rate change.

Referring again toFIG. 2, the compressed data measurement module250provides measurements that are useful for feedback control of the preprocessor210and the signal compression processor220. To provide feedback control, the controller240calculates adjustments to one or more of the control parameters261a,261band271based on the feedback parameters received from input251. In particular, the controller240can provide coordinated control of selected control parameters261aand261bin response to feedback parameters. In an embodiment for feedback control, the controller input processor270calculates the difference between a feedback parameter and a corresponding desired value and provides the resulting error value to the control function processor260. The control function processor260calculates corresponding changes for the selected control parameters CP1and CP2based on the error value. Any changes to the selected control parameters CP1and CP2are determined in accordance with the control function or the ratio parameter. In the above example for the sample rate control parameter312and the dynamic range control parameter322, the controller input processor270determines a bit rate error value by calculating the difference between the measured bit rate provided as a feedback parameter and the desired bit rate. The control function processor260calculates the control parameters CP1and CP2using equations (6) through (9) where the bit rate change in equation (6) is the negative of the bit rate error value. Alternatively, the control function processor260can apply step changes in accordance with equations (1) and (2), as described above. In an embodiment where the control function is represented by a lookup table, as previously described with respect toFIG. 5b, the control function processor260determines the pointer582aor582bbased on the bit rate error value. Each set of values for control parameters CP1and CP2corresponding to each row in the lookup table has an associated bit rate change that can be calculated using methods well known in the art. The control function processor260can use the bit rate error value to select the appropriate bit rate change and the associated set of values for control parameters CP1and CP2.

A control parameter used by the signal compression processor220may also be needed for decompression. The encoder330can encode one or more control parameters and include encoded control parameters with the compressed samples225.FIG. 7is a block diagram of a decompressor that forms reconstructed signal samples777from the compressed samples225. The decoder710performs inverse operations of the encoder330to produce decoded samples711. As described previously with respect toFIG. 3, the encoder330may calculate first or higher order derivatives of the modified signal samples321and/or Huffman or other encoding to form compressed samples225. The decoder710applies Huffman or other decoding to the compressed samples225to form decoded samples711. Alternatively, if the encoder330calculated first or higher order derivatives prior to Huffman or other encoding, the Huffman or other decoding produces decoded derivative samples. The decoder710applies an integrator to the decoded derivative samples to form the decoded samples711. The integrator provides an inverse operation to the first or higher order derivative calculation. If the encoder330applied lossless encoding, the decoded samples711would be identical to the modified signal samples321. If lossy encoding was applied, the decoded samples711would be approximately the same as the modified signal samples321. If control parameters were encoded, the decoder710separates the encoded parameters for decoding by the parameter decoder740. The decompression controller750receives the decoded control parameters741and user input760to determine decompression control parameters for the decoder710, the dynamic range restore module720and the sample rate restore module730. The dynamic range restore module720applies multiplication and/or left-shifting operations to increase the amplitudes of the decoded samples to the original dynamic range. The decompression controller750uses the decoded dynamic range control parameter to determine one or more factors for the multiplication and/or left-shifting operations. Since the dynamic range adjuster320reduced the number of bits for representing the resampled signal samples311, the scaled samples721will be approximations of the resampled signal samples311. The sample rate restore module730resamples the scaled samples721at the original sample rate. A Farrow filter can be used for the resampling operation as described previously for the resampler310. The samples output from the sample rate restore module730are reconstructed signal samples777. As stated previously for the signal compression processor220, the order of the dynamic range restore module and the sample rate restore module can be reversed. Since the operations of the signal compression processor220are lossy, the reconstructed signal samples777are approximations of the original signal samples100.

FIG. 8is a block diagram of an embodiment of the sample rate restore module730that corrects resampling errors. This corresponds to the embodiment of the compressor's resampler310where the resampling error451is calculated, as described with respect toFIG. 4. The error decoder712decodes the encoded error samples included in the compressed samples225to produce decoded error samples713. The decoded error samples713have the original sample rate and correspond to the error samples451inFIG. 4. The decoder710can include the error decoder712. The upsampler732resamples the decoded samples711or the scaled samples721, depending on the order of these operations in the signal compression processor220. FIG.8's decoded samples711or scaled samples721correspond to resampled (downsampled) signal samples311inFIG. 4. The upsampler output samples733have the original sample rate. The delay buffer734delays the decoded error samples so that they have the correct temporal alignment with the upsampler output samples733, thus compensating for processing delays in the upsampler732. The adder736adds each upsampler output sample733with the corresponding decoded error sample735to produce the reconstructed signal samples777.

In alternative embodiments for the compressor, an optional preprocessor210is included to perform filtering, downconversion and other operations to prepare the input signal samples100for compression. The preprocessor210produces signal samples211with lowpass characteristics that can be effectively compressed by the signal compression processor220. Depending on the characteristics of the input signal100, the preprocessor210may selectively reorder and selectively invert signal samples100to form one or more streams of signal samples. The signal compression processor220performs the selected compression operations in accordance with the control parameters on each signal stream. The preprocessor210receives control parameters212from the controller input processor270.

FIG. 9is a block diagram of the preprocessor210. (The '533 patent also describes the preprocessor operations with respect toFIG. 12.) The programmable demultiplexer910reorders the signal samples100into one, two or three demultiplexed signal sample streams911a,911band911cin accordance with a reordering control parameter931. A programmable inverter920a,920band920cfor each demultiplexed signal sample stream911a,911band911cselectively inverts signal samples in accordance with the inversion control parameter933. Each inverter output211a,211band211cprovides a set of demultiplexed input samples for the signal compression processor220. The signal compression processor220applies the selected operations of resampling, dynamic range adjustment and encoding to each set of demultiplexed input samples211a,211band211cto form compressed samples225. Referring toFIG. 3, the resampler310and dynamic range adjuster320can form up to three sets of modified signal samples321. The encoder330applies first or higher order differences to each set of modified signal samples321and/or Huffman or other encoding to form compressed samples225.

FIG. 10gives examples of signal samples and phasor diagrams to illustrate the operations of the programmable demultiplexer910and the programmable inverters920. Beginning with the example of a baseband signal, corresponding to row labeled “Band1” inFIG. 10, the center frequency is near DC (0 Hz) and the phase increase between consecutive samples is less than 10 degrees. The first phasor diagram1010shows that since the phase changes between consecutive samples are small, the magnitudes of the differences of consecutive samples will be relatively small compared to the magnitudes of the samples themselves. The first example sequence1012corresponds to samples of a baseband signal in Band1. Since the differences between consecutive samples are small relative to the sample magnitudes, calculating first or higher order derivatives, or differences, creates derivative samples with smaller data widths than the original samples. Compression using this approach is effective for the baseband (Band1) example inFIG. 3.

FIG. 10also gives examples of sampled signals where the center frequency is above DC, but below the Nyquist frequency, fs/2. For Band2, the center frequency is near fs/6 and the phase increase between consecutive samples is about 60 degrees. The second phasor diagram320shows that pairs of samples separated by 180 degrees, or three sampling intervals, have similar magnitudes but opposite polarities, as illustrated by pairs of samples (1020-0,1020-3), (1020-1,1020-4) and (1020-2,1020-5). Inverting one of the samples in the pair (or multiplying by −1) provides a close estimate of the other sample in the pair. The second example sequence1022also shows that samples separated by three sampling intervals have similar magnitudes and opposite signs. For example, the value of sample1022-0is 32767 and the value of sample1022-3is −32756. For Band2, derivative after selective inversion operations on samples separated by three sampling intervals produce derivative samples with smaller data widths. The smaller data width allows a greater amount of compression.

For the example of Band3inFIG. 10, the center frequency is near fs/4 and the phase increase between consecutive samples is about 90 degrees. The third phasor diagram1030shows that samples separated by 180 degrees, or 2 sampling intervals, have similar magnitude and opposite polarity. The third example sequence1032also shows that every other sample has similar magnitudes and opposite polarities. For Band3, inverting samples separated by two sampling intervals followed by computing their difference will result in derivative samples with smaller data widths that can be encoded more efficiently than the original samples.

For the example of Band4inFIG. 10, the center frequency is near fs/3 and the phase increase between consecutive samples is about 120 degrees. The fourth phasor diagram1040shows that samples separated by 360 degrees, or 3 sampling intervals, will have similar magnitudes. The fourth example sequence1042shows that every third sample has similar magnitudes. In this case, forming a difference between samples separated by 3 sampling intervals will give a derivative sample with a smaller data width that can be encoded more efficiently than the original samples.

For the example of Band5inFIG. 10, the center frequency is fs/2 and the phase increase between consecutive samples is about 180 degrees. The fifth phasor diagram1050shows that samples separated by 180 degrees, or one sampling interval, will have similar magnitudes but opposite polarities. The fifth example sequence1052shows consecutive samples have similar magnitudes and opposite polarities. In this case, inverting every other sample and calculating a difference will form a modified sample with a smaller data width that can be encoded more efficiently than the original samples.

The above examples described forFIG. 10show that data compression can be achieved by performing operations such as inversion followed by subtraction (or addition) or subtraction on signal samples that are separated by 1, 2 or 3 sampling intervals, depending on the ratio of the sample rate to the center frequency. The resulting derivative samples are then encoded to form compressed samples. Similar operations can be applied to samples that are separated by four or more sampling intervals, depending on the ratio of the center frequency to the sample rate, to produce difference samples with smaller data widths than the original signal samples.

FIG. 11shows the operations that the programmable demultiplexer910and programmable inverter920perform based on the center frequency of the signal samples100. The first column1100gives the possible center frequencies for this example. The second column1120gives a corresponding frequency band indicator for each center frequency. The indicators can be used as parameters for the reordering control parameter931and the inversion control parameter933. The third column1130gives the different separations between samples x(i) and x(i-j) at demultiplexer outputs911a,911band911cthat would be produced as a result of reordering control parameter931. The fourth column1140shows the result of inversion under control by inversion control parameter933. When the inverter920is “on” the delayed sample x(i-j) is inverted. The fifth column1150shows the mathematical results if derivatives y(i) are calculated by the encoder330. The derivative samples are functions f[ ] of the demultiplexed input samples x, where the function f[ ] is determined by the selected operations of the resampler310and the dynamic range adjuster320. If resampling operations are performed, the calculation operations for y(i) are selected in accordance with the sample intervals of the resampled signal streams.

FIG. 12gives an example of the results of operations on signal samples100input to the programmable demultiplexer910and the programmable inverter920. The graph1200shows signal samples100with a center frequency of fs,/6. For this example, the programmable demultiplexer910reorders the signal samples100into three sets911a,911band911c, each having samples separated by three sampling intervals. The graphs1111a,1111band1111cshow every third sample starting with the first sample1201, the second sample1202and the third sample1203, respectively. The programmable inverter920for each demultiplexed sample stream911a,911band911cinverts every other sample, in accordance with the control parameter933. The graphs1211a,1211band1211cshow the resulting samples. Each stream of inverter output samples forms a corresponding stream of demultiplexed input samples,211a,211band211c, respectively, for the signal compression processor220. Referring toFIG. 3, the resampler310and dynamic range adjuster320may be applied to each stream of demultiplexed input samples,211a,211band211c, in accordance with their respective control parameters312and322to form three sets of modified signal samples321for the encoder330. The encoder330encodes each set of modified signal samples321to form three sets of compressed samples that can be multiplexed together to form compressed samples225using techniques known to those skilled in the art. The encoder330may apply Huffman encoding or other bit-packing in accordance with the compression control parameter332, as described previously. Alternatively, encoder may calculate first or higher order derivatives of each set of modified signal samples321prior to Huffman encoding.

FIG. 13is a block diagram for decompression that includes inverse operations to the demultiplexing and inverting operations performed by the preprocessor210. The demultiplexer1310separates the compressed samples225into the three sets of compressed samples1311. The decompressor1320decompresses each of the three sets of compressed samples1311, using the operations described previously with respect toFIG. 7, to form three sets of reconstructed signal samples1321, each corresponding to a reconstructed version of demultiplexed input samples211a,211bor211c, respectively. Each set of reconstructed signal samples1321is input to a programmable inverter1330producing reconstructed sample streams1331that correspond to the demultiplexed signals911. The multiplexer1340re-orders the reconstructed sample streams to form reconstructed signal samples777that correspond to the original signal samples100. The decompression controller1350provides control parameters for the demultiplexer1310, decompressor1320, inverter1330and the multiplexer1340. In embodiments where encoded control parameters are included in the compressed samples225, the decompression controller1350recovers the control parameters from the compressed samples225.

In applications that include analog to digital conversion of an input analog signal, an embodiment of the present invention can be included in a compression subsystem that compresses the signal samples produced by the ADC. Compressing the signal samples output from an ADC reduces the bit rate of the samples. The reduced bit rate has several design advantages, including the following:1) reducing the data transfer rate requirements of the ADC interface or allowing more rapid data transfer at the same data transfer rate,2) reducing the number of connections (pins or balls) on an ADC device package,3) if storage of the samples is required, storage capacity can be reduced or more samples can be stored.

Prior to specific processing for the application, a decompression subsystem decompresses the compressed samples to reconstruct the signal samples for application specific processing. These advantages also apply when a compression subsystem compresses signal samples prior to transferring to a DAC. After transfer of the compressed samples, a decompression subsystem decompresses the compressed samples to produce the reconstructed signal samples. The DAC converts the reconstructed signal samples to an analog signal.

FIG. 14is a block diagram of an application that compresses the digital samples produced by an ADC. The ADC1402converts an input analog signal101to signal samples100that are input to the compression subsystem1404. The compression subsystem1404includes at least the signal compression processor220(seeFIG. 2) to produce compressed samples225. Alternative embodiments of the compression subsystem1402can include additional elements shown inFIG. 2depending on the requirements of the application. The compression subsystem1404would further include the controller240when the application requires determining the control parameters261a,261band271. The compression subsystem1404would further include the compressed data measurement module250when feedback control of the signal compression processor220is required. The compression subsystem1404would further include the preprocessor210if the characteristics of the signal samples100in the application require the preprocessing operations previously described. The compression subsystem1404would further include the signal parameter measurement module230when needed by the controller240for determining any of the control parameters. The compression subsystem1404would further include the user interface280if user input is needed for developing, configuring or initializing the system. The compression subsystem1404produces compressed samples225for the ADC interface1406. Depending on the application, the ADC interface can provide the compressed samples to a storage device1408, other operations, another interface or directly to the decompression subsystem1410. The application processor1412performs the operations that would normally occur for the application. Prior to application processor1412, the decompression subsystem1410decompresses the compressed signal samples to form reconstructed signal samples777. Referring toFIG. 7, the decompression subsystem1410includes the decoder710and at least one of the dynamic range restore module720and the sample rate restore module730depending on the operations performed by the compression subsystem1404. The decompression subsystem1410can also include one or more additional elements, including the decompression controller750, the parameter decoder740and the user input module760. When the compression subsystem1404includes a preprocessor210that performs the demultiplexing and inverting operations described with respect toFIG. 9, the decompression subsystem1410would include the elements ofFIG. 13to form the reconstructed signal samples777. The application processor1412performs the operations specific to the application on the reconstructed signal samples777. The embodiments of compression and decompression include simple operations that can be implemented to operate in real time. Implementations of the compression subsystem1404and the decompression subsystem1410can operate in real time, or the rate at which the ADC1402forms the digital signal samples100from the input analog signal101.

FIG. 15is a block diagram of an application that compresses signal samples prior to transfer to a DAC. The application processor1412produces the signal samples100. The compression subsystem1404compresses the signal samples100to form compressed samples225. The compression subsystem1404has alternative embodiments as described above with respect toFIG. 14. Depending on the application, the compressed samples225may be transferred to a storage device1408, other operations, another interface or directly to the DAC interface1510. The DAC interface1510provides the compressed samples to the decompression subsystem1410. The decompression subsystem1410has alternative embodiments as described above with respect toFIG. 14. The decompression subsystem1410provides reconstructed signal samples777to the DAC1520. The DAC converts the reconstructed signal samples to an analog output signal1521. The compression subsystem1404and decompression subsystem1410can be implemented to operate in real time, or the rate at which the DAC1520forms the output analog signal1521from the reconstructed signal samples777.

A data acquisition system can include an embodiment of the present invention. A compression subsystem can be integrated into an application specific integrated circuit (ASIC) that includes an ADC. Alternatively, the compression subsystem can be implemented in a separate device that can be coupled to the output of an ADC chip. The device can include ASIC implementation, a field programmable gate array (FPGA) implementation or a programmable processor, such as a digital signal processor (DSP), microprocessor or microcontroller. Depending on the system architecture, the decompression subsystem may be incorporated in the same device or in a separate device, such as an ASIC, FPGA or programmable processor that may also include the implementation of the application's specific functions.

In an application the where the signal samples are compressed prior to transfer to a DAC, a preferred implementation integrates the compression subsystem into the application's processor using ASIC, FPGA or programmable processor technology. A preferred implementation of the decompression subsystem is an ASIC core in the DAC device.

An embodiment of a GUI for user input to an application can be implemented using programming techniques well known in the art. The GUI can be a permanent part of the application or part of a test system used to configure an embedded application.

FIG. 16illustrates an embodiment of a system that includes a GUI1600connected to a compressor1640. The GUI1600is an embodiment of the user interface280inFIG. 2. The user selects the desired control and configuration for the compressor1640using the graphical constructs of the GUI1600. In this embodiment, the user can select from three operating modes of the compressor1640via compression mode options1610. The selectable options include a lossess compression mode1612, a fixed rate compression mode1614and a fixed quality compression mode1616. The black dot next to the “fixed rate” element1614indicates that the user has selected the fixed rate compression mode. For fixed rate compression mode1614, the user specifies the desired compression ratio1615by entering a numerical value. For example, an entry of 1.9 indicates a desired fixed compression ratio of 1.9:1. When the user selects the fixed quality mode, the GUI1600includes additional input boxes1618a,bfor entry of desired quality parameters. Fixed quality parameter options include values for the sample rate and dynamic range as well as quality parameters for corresponding decompressed, or reconstructed, signal samples including signal to noise ratio, noise floor and bit error rate. The scale600and pointer640, previously described with respect toFIG. 6, in this example are used to select a ratio parameter that will be used to coordinate the sample rate (SR) change and dynamic range (DR) change. The GUI1600can also provide for the entry of other control parameters, including compression control parameters332for control of the encoder330inFIG. 3and preprocessor control parameters212for control of the preprocessor210inFIG. 2. The GUI1600can be implemented in a computer, an embedded microprocessor or a digital signal processor coupled to a display device, or any programmable system having a graphical display.

Input parameters corresponding to the user's selections are transferred via communication channel1620to the compressor1640. The communication channel1620can be a parallel or serial cable, a parallel or serial bus, a wireless channel, an optical connection or other data transfer channel. In this embodiment, the compressor1640includes the signal compression processor220, controller240and compressed data measurement module250and can optionally include the preprocessor210and signal parameter measurement module230previously described. This embodiment also includes an ADC1630that converts an input analog signal101to the signal samples100input to the compressor1640. In alternative embodiments, the ADC1630and compressor1640can be implemented in the same integrated circuit or in a multi-chip module. A multi-chip module contains two or more semiconductor die in one electronic package.

Incorporating embodiments of the present invention in a system may increase the gate count and power consumption. However, the benefits of compression will decrease other system costs, such as the cost of storage to capture the compressed samples or the cost of a bus or network to transfer the compressed samples to decompressor.