Abstract:
A highly-programmable Finite Impulse Response (FIR) digital filter overcomes the limitations of conventional configurations. Specifically, a compound FIR filter configuration is provided, offering the advantages of heightened programmability in both transfer function coefficients hf, hg and in degree of interpolation; distribution and sharing of resources between F and G filter portions, mode-switching capability between high-pass and low-pass modes, and programmable truncation/saturation.

Description:
BACKGROUND OF THE INVENTION  
         [0001]    In conventional Finite Impulse Response (FIR) digital filter configurations, as a result of interpolation of an input signal, high-order images are generated at multiples of the interpolation sampling rate. Such conventional “unitary” filters that seek to provide the combined goals of superior filter characteristics (stop band, passband, transition band) with needed suppression of the high-order images, are complicated in configuration, as they require high-order design, and are therefore expensive to implement.  
           [0002]    For this reason, a new “compound” filter configuration has recently evolved, wherein the interpolation and suppression functions are partitioned into separate filters: a first portion, referred to as the interpolation, or “F”, filter, being optimized for superior frequency discrimination characteristics; and a second portion, referred to as the masking, image suppression, or “G”, filter, being optimized to suppress higher order images. The resulting compound transfer function of the F and G components provides superior overall filter characteristics using two relatively lower-order filters. By distributing the F and G functions, and optimizing each individually, the performance of the collective configuration is at least comparable to that of conventional unitary configurations, while simplifying hardware complexity, as lower-order filters can be employed.  
           [0003]    [0003]FIG. 1A is a schematic block diagram of a contemporary compound high-pass FIR filter. Digital data is received at input  26 . The data is processed by an interpolation filter  20  whose transfer function F is represented by the following relationship:  
               y                   f        [   n   ]         =       ∑   kf          (     h                   f        [     k                 f     ]       ×     x        [     n   -     (     N   ×   k                 f     )       ]         )               (   1   )                               
 
           [0004]    where x(n) represents the input data, hf represents impulse response coefficients for the F filter, kf represents the coefficient count for the F filter, N represents the interpolation value for the F filter; and yf[n] represents data output from the F filter.  
           [0005]    Data  28  output from the interpolation filter  20  is processed by a masking filter  22  whose transfer function G is represented by the following relationship:  
               y                   g        [   n   ]         =       ∑     k                 g            (     h                   g        [     k                 g     ]       ×     x        [     n   -     k                 g       ]         )               (   2   )                               
 
           [0006]    where x(n) represents data input to the G filter, hg represents impulse response coefficients for the G filter; kg represents the coefficient count for the G filter; and yg[n] represents data output from the G filter.  
           [0007]    A feed forward path in the form of a subtractor  30 , with delay function  24 , is configured as shown in FIG. 1A to provide for alternative frequency discrimination settings (e.g., high-pass, band pass, band stop, etc. ) in the FIR filter. Otherwise, as shown in FIG. 1B, absent the subtractor  30  and the feed forward path, the FIR filter operates as a low-pass filter.  
           [0008]    It can be seen in the above Equations 1 and 2 that each iteration of the summation requires a multiplication operation, which can be costly in terms of processing time and hardware complexity. As explained above, the compound filter configuration distributes the interpolation and masking processes into separate F and G functions, which reduces complexity of each separate function, as compared to the conventional combined function. For this reason, the F and G filters are relatively low-order, and therefore have a relatively lower number of impulse response coefficients hf, hg, referred to in the art as “taps”. With relatively fewer taps, the filter functions rely on fewer multiplication operations, and therefore processing time is improved, and hardware complexity is reduced .  
           [0009]    While offering the above advantages, current compound filter configurations employ F and G filters that are limited to fixed coefficients. For this reason, the overall filter transfer function is fixed at the time of fabrication, and therefore the filter is not adaptable to variances in environment or data. In addition, the overall system throughput is limited by the filter having the highest number of taps.  
         SUMMARY OF THE INVENTION  
         [0010]    The present invention provides a highly-programmable Finite Impulse Response (FIR) digital filter that overcomes the limitations of conventional configurations. Specifically, the present invention provides a compound FIR filter configuration, offering the advantages of heightened programmability in both transfer function coefficients hf, hg (both in number and value), and in degree of interpolation; distribution and sharing of resources between F and G filter portions, and advanced truncation. The present invention further provides for optional programmability between various frequency discrimination settings (e.g., high-pass, bandpass, etc).  
           [0011]    In a first aspect, the present invention is directed to a compound filter for processing digital data. A first filter portion includes first computational resources for performing a first filter function. A second filter portion includes second computational resources for performing a second filter function. At least one of the first and second filter portions is configured to access and utilize the computational resources of the other filter portion for performing the filter function.  
           [0012]    In one embodiment, the first and second filter portions each include a data bank having a plurality of data nodes, a coefficient bank for storing filter coefficients, a multiplier for multiplying filter data stored in the data nodes by corresponding filter coefficients stored in the coefficient bank, resulting in product data, and an accumulator for summing the product data to produce filtered data.  
           [0013]    The data bank may include a negative data bank having negative data nodes, a positive data bank having positive data nodes, and an adder for summing filter data contained in corresponding positive and negative data nodes prior to multiplication with the corresponding filter coefficient. The data nodes may comprise data registers, or may comprise memory locations referenced by pointers. The first filter portion may comprise an interpolation filter or a masking filter.  
           [0014]    The first filter portion may include a first number of filter nodes and the second filter portion may include a second number of filter nodes and the first and second filter portions may share their respective resources when the first number and second number are different. The resources may comprise an adder, a multiplier, and an accumulator. The first and second filter functions are determined by programmable filter coefficient values and count, and interpolation. The resources may include a programmable truncation unit for performing saturation, truncation, and rounding of the outputs the first and second filter portions.  
           [0015]    A delay unit may be coupled between an output of the second filter portion and an input of the first filter portion such that the compound filter is configured as a different frequency discrimination filter (e.g., high-pass filter). A programmable switch may be coupled to the delay unit for activating the delay unit such that the filter system is operable at various frequency discrimination settings, depending on the switch position.  
           [0016]    In another aspect, the present invention is directed to a method for processing digital data in a compound filter. A first filter function is performed in a first filter portion having first computational resources. A second filter function is performed in a second filter portion having second computational resources. At least one of the first and second filter portions is configured to access and utilize the computational resources of the other filter portion for performing the filter function. 
       
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0017]    The foregoing and other objects, features, and advantages of the invention will be apparent from the more particular description of preferred embodiments of the invention, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention.  
         [0018]    [0018]FIGS. 1A and 1B are schematic block diagrams of a compound Finite Impulse Response (FIR) filter configured as high-pass and low-pass filters, respectively.  
         [0019]    [0019]FIG. 2 is a detailed schematic block diagram of a compound FIR filter configured in accordance with the present invention.  
         [0020]    [0020]FIG. 3 is a flow diagram illustrating the sharing of resources between F and G portions of the FIR filter, in accordance with the present invention.  
         [0021]    [0021]FIG. 4 is a schematic block diagram of a compound FIR filter including a programmable feed forward loop for switching between various frequency discrimination modes (e.g. low-pass, high-pass, etc.), in accordance with the present invention.  
         [0022]    [0022]FIG. 5 is a flow diagram illustrating determination of read pointer values, in accordance with the present invention.  
         [0023]    [0023]FIG. 6 is a flow diagram illustrating determination of initial read pointer values for the negative data bank, in accordance with the present invention.  
         [0024]    [0024]FIG. 7 is a flow diagram illustrating determination of initial read pointer values for the positive data bank, in accordance with the present invention.  
         [0025]    [0025]FIG. 8 is a flow diagram illustrating determination of write pointer values for the negative data bank, in accordance with the present invention.  
         [0026]    [0026]FIG. 9 is a flow diagram illustrating determination of write pointer values for the positive data bank, in accordance with the present invention.  
         [0027]    [0027]FIG. 10 is a flow diagram illustrating determination of the pointer value for the center data address, in accordance with the present invention.  
         [0028]    [0028]FIG. 11 is a flow diagram illustrating the implementation of the delay block  24  for the high-pass filter node illustrated in FIG. 1A, in accordance with the present invention.  
     
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS  
       [0029]    [0029]FIG. 2 is a detailed schematic block diagram of a compound FIR filter configured in accordance with the present invention. An F-filter (for example, interpolation filter) portion  20  includes an F-filter data bank  40 , an adder  44 , a multiplier  46 , an F-filter coefficient bank  48 , an accumulator  50 , and truncation/saturation hardware  52 . Similarly, a G-filter (for example, masking) portion  22  includes a G-filter data bank  54 , an adder  60 , a multiplier  64 , a G-filter coefficient bank  62 , an accumulator  66 , and truncation/saturation hardware  68 . The truncation/saturation hardware  52 ,  68  of the F-filter and G-filter may optionally be combined into a single unit whose resources are shared by the F and G filters  20 ,  22 . Input data  26  is received, processed by the F-filter  20 , and the F-filter processed data  28  is provided to, and processed by, the G-filter  22 , resulting in output data  23 .  
         [0030]    The F-filter data bank  40  includes a plurality of data registers  42 , or memory locations, for temporary storage of the input data fx k . The data  26  are input into the data bank, and at each cycle, progress to the next data bank memory location  42 , as shown. Either the data itself may be shifted, for example by shift register, or else pointers to the memory locations where the data are stored may be appropriately controlled, to keep the data locations current. A detailed example of pointer control and maintenance is provided below.  
         [0031]    For each time value k, the data fx k  are multiplied by their corresponding F-filter coefficient values hf k  at multiplier  46 . Assuming that the filter is symmetric for values of +k and −k, the number of multiplication operations may be essentially halved by first adding the values of the positive and negative data nodes fx k  and fx −k  at adder  44  and multiplying the sum by the corresponding F-filter coefficient value hf k  at multiplier  46 , according to the relationship:  
               y        [   n   ]       =       ∑     k   =     -   N1       N1          h                   f        [   k   ]       ×     x        [     n   -     (     N   -   k     )       ]                   (   3   )                               
 
         [0032]    for the general case, and  
               y        [   n   ]       =       h                   f        [   0   ]       ×     x        [     n   -   N     ]         +       ∑     k   =   1     N1          h                   f        [   k   ]       ×     {       x        [     n   -     (     N   -   k     )       ]       +     x        [     n   -     (     N   +   k     )       ]         }                   (   4   )                               
 
         [0033]    for the case where the impulse response is symmetric.  
         [0034]    The result of each multiplication is accumulated in accumulator  50  for all k values, and the resulting F-filtered data  28  is provided to the G-filter  22 .  
         [0035]    Similarly, the G-filter data bank  54  includes a plurality of data registers, or memory locations  56 , for temporary storage of the input data gx k . The data  28  are input into the data bank  54 , and at each cycle, progress to the next data bank location  56 , as shown. As described above, either the data itself may be shifted, or pointers to the memory locations where the data are stored may be adjusted to keep the data locations current.  
         [0036]    For each time value k, the data gx k  are multiplied by their corresponding G-filter coefficient values hg k  at multiplier  64 . Note that since the G-filter performs a different function than the F-filter, its coefficients are different. Assuming the G-filter transfer function to be symmetric for values of +k and −k, the number of multiplication operations may be essentially halved by first adding the positive and negative data values gx k  and gx −k  at adder  60  and multiplying the sum by the corresponding G-filter coefficient value hg k  at multiplier  64 , according to the relationship:  
               y        [   n   ]       =       ∑     k   =     -   N2       N2          h                   g        [   k   ]       ×     x        [     n   -   k     ]                   (   5   )                               
 
         [0037]    for the general case, and  
               y        [   n   ]       =       h                   g        [   0   ]       ×     x        [   n   ]         +       ∑     k   =   1     N2          h                   g        [   k   ]       ×     {       x        [     n   -   k     ]       +     x        [     n   +   k     ]         }                   (   6   )                               
 
         [0038]    for the case where the impulse response is symmetric.  
         [0039]    In many compound filtering applications utilizing the above configuration, it is common to have different order numbers, (also referred to as “taps”, or “k” values) in the F and G filters. Assuming this, the filters may be performing different numbers of multiplication operations, and therefore, data processing by one filter may be under greater, or less, computational demand relative to the other. Since the filters effectively operate on the data in a serial process, this difference means that there are times when system resources are not fully utilized. For example, one filter may have a dormant data path while waiting for the other filter to complete its processing.  
         [0040]    The present invention addresses this issue by sharing such resources between the F and G filters. In other words, when it is determined that one filter requires more multiplication operations than the other filter, then the filter having extra resources temporarily lends its resources to the other filter, leading to more efficient system operation.  
         [0041]    Referring to FIG. 3, which is a flow diagram in accordance with the present invention, the sharing of resources between F and G portions of the FIR filter is illustrated. This embodiment is particularly applicable to a filter bank application that employs pointers for managing the locations of the input data.  
         [0042]    Initially, a user employs a high-level modeling tool to determine a desired filter shape. The tool in turn generates parameters that define the desired F and G FIR digital filters. Such parameters may include, for example, the number of coefficients for the F and G filters, coefficient values for the F and G filters, an interpolation value of the F filter, saturation, truncation and rounding values of the F and G filters, and a mode value for programming various frequency discrimination settings.  
         [0043]    At initialization, the program parameters are input, at step  102 , to the filter system of the present invention. The parameters may be stored, for example in on-board or on-chip Random Access Memory (RAM) or Read-Only Memory (ROM), or a programmable register bank may otherwise be provided by a user. The burden of the filter on system resources is determined based on the parameters, which in turn determine the number of multiplications required for each filter at each input data sample period, and based on this, it is determined whether the F-filter is to share resources with the G-filter, whether the G-filter is to share resources with the F filter, or whether no sharing is required.  
         [0044]    In each instance, memory is allocated for the G-filter and the F-filter input data, and referenced by pointers that access the memory locations. In a preferred embodiment, the memory allocated for the F-filter comprises dual-port RAM, while the memory allocated for the G-filter may comprise a register bank having a multiple data path. Such a configuration allows for sharing of resources between the filters, while minimizing occupation of integrated circuit real estate. With reference again to FIG. 2, assuming that the memory bank  40  for the F-filter data  42  comprises a dual port memory having dual address and data lines for access to memory locations, the first port, port 1, may be configured to transfer data to the adder  44  and multiplier  46  local to the F-filter  20 , while the second port, port 2, may be configured to transfer the data to the adder  60  and multiplier  64  local to the G-filter  22 . In this manner, both the positive and negative data nodes  100 A,  100 B respectively can be ported over to utilize the resources of the G-filter  22 , while at the same time, the coefficients  48  (which, for example, can also be stored in dual-port RAM) pertaining to the F-filter  20  are also ported over to the G-filter  22  to enable multiplication of the F-filter data with the F-filter coefficients utilizing the G-filter multiplier  64 . A storage capability, again either in the form of a register or pointer-managed memory, stores values obtained by a filter&#39;s independent calculations, while its resources are shared with the other filter. In a preferred embodiment, the storing, sharing, and maintenance of the data and coefficients of each filter are controlled through the use of pointers controlled to refer to specific memory locations in the dual-port memory bank.  
         [0045]    Returning to FIG. 3, “wrap-around” values pertaining to the number of pointers required for the F and G filters, are calculated for: 1.) the F-filter&#39;s independent calculations, 2.) the F-filter&#39;s shared calculations, 3.) the G-filter&#39;s independent calculations, and 4.) the G-filter&#39;s shared calculations as shown in step  104 . The calculation of the wrap-around values is described in further detail below.  
         [0046]    Based on the input parameters received at step  102 , it is determined whether the G-filter is to share resources with F-filter  105 , whether the F-filter is to share resources with the G-filter  107 , or whether no sharing of resources is required  109 . Assuming that the G-filter is to share resources with F-filter  105 , initially, the F-filter&#39;s independent calculations are performed using F-filter&#39;s resources, and G-filter&#39;s independent calculations are performed using G-filter&#39;s resources, as shown in step  106 . Next, the results of the G-filter&#39;s calculations are stored in a temporary register  108 . In step  110 , the F-filter&#39;s independent calculations are continued using the F-filter&#39;s resources and, in addition, G-filter&#39;s resources are used to complete the portion of F-filter&#39;s remaining calculations, as shown in shown in  110 . At the next sample period, the cycle repeats by performing the independent calculations of the respective filters  106 , followed by steps  108 ,  110 .  
         [0047]    Alternatively, if it is determined that the F-filter is to share resources with the G-filter,  107 , a similar resource-sharing procedure applies, by initially performing the F-filter&#39;s and G-filter&#39;s independent calculations using their respective resources  114 , by storing the F-filter&#39;s results in a temporary register  116 , and by sharing the F-filter&#39;s resources to complete a portion of the G-filter&#39;s remaining calculations  118 , as described above.  
         [0048]    In the event that no resource sharing is required  109 , the independent calculations of F-filter are performed by F-filter&#39;s resources and the independent calculations of the G-filter are performed by the G-filter&#39;s resources at each sample period  112 .  
         [0049]    With reference to FIG. 2, filter operation in the preferred embodiment of the present invention is dependent on the address generation of data bank pointers, which include read pointers for reading data from the negative and positive data node banks of the F- and G-filters  100 A,  100 B,  101 A,  101 B and write pointers for writing data into the negative and positive data node banks of the F- and G-filters  100 A,  100 B,  101 A,  101 B; center data pointers for reading data from the center data nodes of the F- and G-filters  42 A,  56 A (the center data nodes  42 A,  56 A being preferably affiliated with the negative data node banks  100 A,  101 A); a high-pass subtract data pointer for reading data from the positive data node bank of the F-filter  100 B from which is subtracted the output  23 , when the high-pass filter mode is activated; and coefficient bank pointers for reading coefficients from the F- and G-filter coefficient banks  48 ,  62 .  
         [0050]    Pointer operation is described below with the assistance of the pointer update flow diagrams described below with reference to FIGS.  5 - 11 . Determination of the coefficient bank pointers utilizes a simple linearly incrementing address calculated during each sample period for the number of multiplies required to complete the calculation. For example, the addresses may increment from an initial value of 1 to the coefficient count for the filter. Under conditions of symmetry, as assumed in this embodiment, the total coefficient count is an odd number, and the number of coefficients loaded in each coefficient bank is represented by:  
         [(Total_Codcient_Count)/2]+1  (7)  
         [0051]    where the “+1” quantity arises from the coefficient used for the multiplication of the center data, while “[(Total_Coefficient_Count)/2]” refers to the coefficients used for multiplication with the data bank pre-adder  44  outputs. Symmetry allows for a halving of the number of multiplication operations.  
         [0052]    The wrap-around value of a pointer of each filter is based on the number of coefficients  48 , 62  used by the filter. For the F-filter, the wrap-around value of the pointer is further based on the interpolation value of the filter. As described above, and referring to FIG. 2, the data path for each filter  40 ,  54 , is partitioned into negative and positive data nodes:  100 A,  101 A being the negative data nodes for the F and G filters, respectively, and  100 B,  101 B being the positive data nodes for the F and G filters respectively.  
         [0053]    Wrap-around values are calculated to determine the address value at which a memory pointer will wrap around to the initial memory location address value designated for the filter. In a preferred embodiment, the wrap-around values are calculated according to the following relationships:  
         [0054]    for the F-filter:  
           wavf 1=((FCoeffCntAdjust)×(FPtrIncVal+1)−1  (8)  
           wavf 2=((FCoeffCnt)×(FPtrIncVal+1)−1  (9)  
         [0055]    where waf1 and waf2 represent the first and second wrap-around values for the F-filter, and wherein FcoeffCnt represents the coefficient count defined for the F-filter and wherein FCoeffCntAdjust is equal to the FCoeffCnt if the coefficient count is less than a fixed number, for example the number of clock cycles in the sample period available for performing multiply operations, or else is set equal to the fixed number; and where in FptrIncVal represents the F-filter interpolation value.  
         [0056]    Similarly, for the G-filter the first and second wraparound values are calculated as follows:  
           wavg 1=(GCoeffCntAdjust)−1  
           wavg 2=(GCoeffCnt)−1  (10), (11)  
         [0057]    where GcoeffCnt represents the coefficient count defined for the G-filter and wherein GcoeffCntAdjust is set equal to the GCoeffCnt value if the coefficient is less than a fixed number, for example the number of available clock cycles in the sample period for performing multiply operations, otherwise it is set to the fixed number.  
         [0058]    Following calculation of the wrap-around values, read and write pointers are determined for each of the positive and negative data banks for each of the F and G filters. The pointer values continually evolve as data processing is conducted, since the pointer values determine not only the mapping of data values within a filter, but also the mapping of data values between filters as their resources are shared.  
         [0059]    The following is an example of the operations involved in the various pointer calculations.  
         [0060]    Assume each data sample period to be 16 clock cycles, which limits the number of multiplication operations for each data path to be a number less than 16, for example 14. Assume also that the filter impulse responses are symmetric, which allows for a halving of the number of multiplication operations (with the exception of the center coefficient multiplication, which is singled out and handled separately).  
         [0061]    Assume also that the F-Filter&#39;s coefficient count is 35, and therefore the number of multiplication operations is [(35−1)/2+1]=18 (refer to Equation 7). It follows that FcoeffCnt=18−1=17; FcoeffCntAdjust=13. The parameter FcoeffCnt is set to 17 since the total number of multiplication operations required by the filter is 18, and since the center data is read and written using a separate pointer. The parameter FcoeffCntAdjust is set to 13 since the maximum number of multiplications available in the sample period is 14, and since the center data is read and written using a separate pointer.  
         [0062]    For the G-Filter, assume the coefficient count to be 19, and therefore the number of multiplication operations required is 10, while GcoeffCnt=10−1=9; GcoeffCntAdjust=9. The parameter GcoeffCnt is set to 9 since the total number of multiplication operations required by the filter is 10, and since the center data is read and written using a separate pointer. The parameter GcoeffCntAdjust is also set to 9 since the G filter can be implemented in less than 14 cycles.  
         [0063]    Assume also that the F-filter interpolation value is 7, and it follows that FptrIncVal=7−1=6.  
         [0064]    In view of the above assumptions, the G-filter is made to share resources with the F-filter, since the G-filter has a number of dormant clock cycles after it completes its own calculations in a 16-clock-cycle data sample period. Referring to the above equations, wavf1=(13*7)−1=90, wavf2=(17*7)−1=118, wavg1=9−1=8; wavg2=9−1−8.  
         [0065]    Table 1 depicts the calculation of initial values for the read pointer addresses in the F-filter for sample periods 1-115:  
                                                                       TABLE 1                       Data Sample Period Number   1   2   3   4    5    6    7    8    9   . . .   112   113   114   115                   F-Filter Negative Data Bank   6   7   8   9   10   11   12    13    14   . . .   117   118    0    1       Address Initial Value (FIG. 6)       F-Filter Positive Data Bank   6   5   4   3    2    1    0   118   117   . . .    14    13   12   11       Address Initial Value (FIG. 7)                  
 
         [0066]    Table 2 depicts the calculation of initial values for the read pointer addresses in the pointers in the G filter for sample periods 1-99:  
                                                                       TABLE 2                           Data Sample Period Number   1   2   3   4   5   6   7   8   9   10   11   12   13   14               G-Filter Negative Data Bank   0   1   2   3   4   5   6   7   8   0    1   2   3   4       Address Initial Value (FIG. 6)       F-Filter Negative Data Bank   97   98   99   100   101   102   103   104   105   106   107   108   109   110       Address Initial Value (shared)       G-Filter Positive Data Bank   0   8   7   6   5   4   3   2   1   0    8   7   6   5       Address Initial Value (FIG. 7)       F-Filter Positive Data Bank   97   96   95   94   93   92   91   90   89   88    87   86   85   84       Address Initial Value (shared)               Data Sample Period Number   15   16   17   18   19   20   21   22   23   24   . . .   97   98   99               G-Filter Negative Data Bank   5   6   7   8   0   1   2   3   4   5   . . .   6   7   8       Address Initial Value (FIG. 6)       F-Filter Negative Data Bank   111   112   113   114   115   116   117   118   0   1       74   75   76       Address Initial Value (shared)       G-Filter Positive Data Bank   4   3   2   1   0   8   7   6   5   4   . . .   3   2   1       Address Initial Value (FIG. 7)       F-Filter Positive Data Bank   83   82   81   80   79   78   77   76   75   74   . . .   1   0   118       Address Initial Value (shared)                  
 
         [0067]    where the first value for each data element (i.e. “0” for sample period 1) represents the initial value used for determining the address for the G-filter&#39;s calculations, while the second value (i.e. “97” for sample period 1) represents the initial value used for determining the address for the F-filter&#39;s calculations, when the G-filer is sharing resources with the F-filter.  
         [0068]    Table 3 illustrates a progression by clock cycle of the read pointer values for the F- and G-filters, for sample period 1:  
                                                                             TABLE 3                           (see FIG. 5)            Clock Cycle   1   2    3    4    5    6    7    8    9   10    11    12    13   14               F-Filter Negative Data Bank   na   6   13   20   27   34   41   48   55   62    69    76    83   90       Address Value       F-Filter Positive Data Bank   na   6   13   20   27   34   41   48   55   62    69    76    83   90       Address Value       G-Filter Negative Data Bank   na   1    2    3    4    5    6    7    8   97   104   111   118   na       Address Value       G-Filter Positive Data Bank   na   1    2    3    4    5    6    7    8   97   104   111   118   na       Address Value                  
 
         [0069]    Clock cycle 1 is reserved for the multiplication of the center node data  42 A,  56 A. The F-filter pointer value increments by 7 due to the interpolation value. No interpolation is present in the G-filter. During cycle 10, the G-filter has completed all multiplication operations, so it now lends resources to the F-filter. At cycle 14, all calculations have been completed in the G-filter, so the resources are dormant for that cycle.  
         [0070]    Similarly, Table 4 applies to the progression by clock cycle of the pointer values for the F- and G-filters, for sample period 2:  
                                                                             TABLE 4                           (see FIG. 5)            Clock Cycle   1   2    3    4    5    6    7    8    9   10    11    12    13   14               F-Filter Negative Data Bank   na   7   14   21   28   35   42   49   56   63    70    77    84   91       Address Value       F-Filter Positive Data Bank   na   5   12   19   26   33   40   47   54   61    68    75    82   89       Address Value       G-Filter Negative Data Bank   na   2    3    4    5    6    7    8    0   98   105   112    0   na       Address Value       G-Filter Positive Data Bank   na   0    1    2    3    4    5    6    7   96   103   110   117   na       Address Value                  
 
         [0071]    Table  5  depicts the pointer values for the center data address in the F- and G- filters for sample periods 1-123:  
                                                                         TABLE 5                           (see FIG. 10)            Data Sample Period Number   1   2   3   4   5   6   7   8   9   10   11   12   13               F-Filter Center Pointer Value   118   0   1   2   3   4   5   6   7   8   9   10   11       G-Filter Center Pointer Value   8   0   1   2   3   4   5   6   7   8   0   1   2               Data Sample Period Number   14   15   16   17   . . .   116   117   118   119   120   121   122   123               F-Filter Center Pointer Value   12   13   14   15   . . .   114   115   116   117   118   0   1   2       G-Filter Center Pointer Value   3   4   5   6   . . .   6   7   8   0   1   2   3   4                  
 
         [0072]    Table 6 depicts the pointer values for the subtract data address with respect to the F-filter for data sample periods 1-13:  
                                                                         TABLE 6                           (see FIG. 11)            Data Sample Period Number   1   2   3   4   5   6   7   8   9   10    11    12    13               F-Filter Subtract Addr. Ptr Value   9   8   7   6   5   4   3   2   1    0   118   117   116                  
 
         [0073]    Table 7 depicts the progression of the write address pointer values for the F- and G-filter for sample periods 1-13:  
                                                                       TABLE 7                       Data Sample Period Number    1    2    3    4    5    6    7    8    9    10    11    12    13    14                   F-Filter Negative Data Bank   118    0    1    2    3    4    5    6    7    8    9    10    11    12       Write Pointer Value (FIG. 8)       F-Filter Positive Data Bank    0   118   117   116   115   114   113   112   111   110   109   108   107   106       Write Pointer Value (FIG. 9)       G-Filter Negative Data Bank    8    0    1    2    3    4    5    6    7    8    9    0    1    2       Write Pointer Value (FIG. 8)       G-Filter Positive Data Bank    0    8    7    6    5    4    3    2    1    0    8    7    6    5       Write Pointer Value (FIG. 9)                  
 
         [0074]    The F-filter&#39;s negative data bank  100 A receives incoming filter data. Similarly, the F-filter&#39;s center node  42 A receives data from the negative data bank  100 A, and the positive data bank  100 B receives data from the center node  42 A. The data then progresses through the G-filter&#39;s negative data bank  101 A, center node  56 A, and positive data filter bank  101 B. The data “progression”, in this example, is implemented through the use of pointers such that data need not be actually moved at each clock cycle, except in the center data node, where the center data register is actually loaded with the latest value, during each data sample period.  
         [0075]    The wrap-around values for which filter indicate the maximum value that a given address pointer will increment to before it “wraps-around” to the appropriate initial value, as shown in the flow diagrams.  
         [0076]    [0076]FIG. 5 is a flow diagram illustrating determination of read pointer values. This flow applies to the positive and negative filter banks  100 A,  100 B,  101 A,  101 B for both F- and G-filters. Initially, a wrap-around value is determined as described above, at step  200 . Next, a start value for the read pointer is calculated at step  202 . This start-value calculation is described in further detail below with reference to FIGS. 6 and 7 for the positive and negative filter data banks respectively. At step  204  it is determined whether the current read pointer plus the increment value exceeds the wrap-around value WAV2. If so, the read pointer is adjusted by the increment value minus the wrap-around value at step  206 . If not, the read pointer is adjusted by the increment value. At the end of the cycle  210 , for example at the end of the data sample period, i.e.  16  clock cycles, a new initial pointer value is determined at step  202 . Otherwise, the process continues at step  204 .  
         [0077]    While the values of the read address pointer can be represented in a single flow diagram, it should be kept in mind that each pointer is capable of providing for the calculations of the local filter, or of the other filter. In view of this, the wrap-around value for each must be set accordingly. So, with reference to FIG. 5, the WAV value applies to the F-filter for the F-filter&#39;s calculations, and applies to the G-filter for the G-filter&#39;s calculations. Similarly, the pointer increment value is different for the respective F- and G-filters (i.e., 0 for the G-filter, and (F-filter interpolation value −1) for the F-filter).  
         [0078]    [0078]FIG. 6 is a flow diagram illustrating determination of the initial value for the read pointer for the negative data banks  100 A,  101 A in accordance with step  202  of FIG. 5. At the start of a data frame, it is determined whether filter resources are currently being shared at step  212 . If so, the pointer increment value is added to the first wrap-around value at step  214 . If not, the pointer increment value is loaded as the read pointer start value at step  216 . At step  218 , the process waits for the end of the cycle. When the end of the cycle is reached, it is determined whether the second wrap-around value has been exceeded at step  224 ; if not, the pointer start value is incremented at step  222 , if so, the pointer start value is reset to zero at step  220 .  
         [0079]    Similarly, FIG. 7 is a flow diagram illustrating determination of the initial value for the read pointer for the positive data banks  100 B,  101 B in accordance with step  202  of FIG. 5. At the start of a data frame, it is determined whether filter resources are currently being shared at step  226 . If so, the pointer increment value is added to the first wrap-around value at step  228 . If not, the pointer increment value is loaded as the start pointer value at step  230 . At step  232 , the process waits for the end of the cycle. When the end of the cycle is reached, it is determined whether the pointer start value has reduced to zero at step  238 ; if not, the pointer start value is decremented at step  236 , if so, the pointer start value is reset to the second wrap-around value at step  234 .  
         [0080]    [0080]FIG. 8 is a flow diagram illustrating determination of write pointer values for the negative data banks  100 A,  101 A. At step  240 , the write pointer is initially set to the second wrap-around value. At step  242 , the process waits for the end of the cycle. When the end of the cycle is reached, it is determined at step  244  whether the write pointer is equal to the second wrap-around value; if not, the write pointer is incremented at step  246 ; if so, the write pointer is reset to zero at step  248 .  
         [0081]    [0081]FIG. 9 is a flow diagram illustrating determination of write pointer values for the positive data banks  100 B,  101 B. At step  250 , the write pointer is initially set to zero. At step  252 , the process waits for the end of the cycle. When the end of the cycle is reached, it is determined at step  254  whether the write pointer is equal to zero; if not, the write pointer is decremented at step  258 ; if so, the write pointer is reset to the second wrap around value at step  256 .  
         [0082]    [0082]FIG. 10 is a flow diagram illustrating determination of the pointer value for the center data address pointing to the negative data banks  100 A,  101 A. At step  260 , the center data pointer is initially set to the second wrap-around value. At step  262 , the process waits for the end of the cycle. When the end of the cycle is reached, it is determined at step  264  whether the center data pointer is equal to the second wrap- around value; if not, the center data pointer is incremented at step  268 ; if so, the center data pointer is reset to zero at step  266 .  
         [0083]    [0083]FIG. 11 is a flow diagram illustrating the implementation of the delay block  24  for the high-pass filter node illustrated in FIG. 4, which is related to the data in the positive bank  100 B of the F-filter  20 , in accordance with the present invention. Particularly, the flow diagram of FIG. 11 provides a process by which the delay function is implemented based on the determination of a delay address pointer pointing to a memory location at which the data is stored. For example, the delay function may be determined based on data propagating through the positive nodes  100 B of the F-filter data bank  40 . At step  270 , the delay address pointer is initially set to the second filter bank&#39;s coefficient count. At step  272 , the process waits for the end of the cycle. When the end of the cycle is reached, it is determined at step  274  whether the delay pointer is equal to zero; if not, the delay pointer is decremented at step  278 ; if so, the delay pointer is reset to the second wrap around value of the F-filter at step  276 .  
         [0084]    [0084]FIG. 4 is a schematic block diagram of a compound FIR filter including a programmable feed forward loop for switching between low-pass and high-pass filter modes, in accordance with the present invention. In this embodiment, a programmable switch  34  is provided, which, when activated, provides a high-pass filter configuration. When deactivated, a low-pass filter configuration is provided. The switch  34  is programmed according to system parameters received at step  102  of FIG. 3.  
         [0085]    While this invention has been particularly shown and described with references to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made herein without departing from the spirit and scope of the invention as defined by the appended claims.