nils-herrmann/clean_scirepeval huggingface dataset:
A spectral entropy-based measure for performance evaluation of a first-order differential microphone array

For differential microphone arrays, most of the performance evaluation measures that are used in the context of noise reduction are based on the energy of the signal. In this paper, we propose a spectral entropy-based measure, which quantifies the ratio of the spectral information contained in the desired and actual outputs of the microphone array, and can evaluate the performance in terms of the average of lost/gain information. At the same time, the value of the spectral entropy-based measure shows whether a speech signal is noisy or if some information has been lost. The proposed measure provides some advantages over the energy-based measures, such as the array gain. Moreover, the performance of a first-order-differential microphone array designed based on the maximum value of the array gain is evaluated using the proposed spectral entropy-based measure.
A high-speed residue-to-binary converter and a scheme for its VLSI implementation

In this paper, a high-speed residue-to-binary converter for the recently introduced moduli set (2/sup k/, 2/sup k/-1, 2/sup k-1/-1) is proposed. Compared to the previous converter based on this moduli set, the proposed one is 40% faster; also, the time-complexity product is improved by 20%. Following the VLSI design flow established by the Canadian Microelectronics Corporation, the proposed converter is implemented in 0.5-micron CMOS technology. Based on this moduli set, layouts of the 8-bit, 16-bit, 32-bit and 64-bit residue-to-binary converters which can be used in further RNS system designs, are generated and simulation results obtained.
Residue to binary number converters for three moduli set

In this paper, residue to binary number converters for the special moduli sets (2n,2n+1,2n+2) and (2n-1,2n,2n+1) are studied. Errors in previous publications have been pointed out. New and more efficient converters for both special moduli sets are proposed. Larger multipliers in previous methods are replaced by smaller multipliers and adders. The new converters use about one-half of the hardware required by previous methods.
Optimal Packet Scheduling for Multi-Description Multi-Path Video Streaming Over Wireless Networks

As developments in wireless networks continue, there is an increasing expectation with regard to supporting high- quality real-time video streaming service in such networks. The recent advances in multi-description (MD) multi-path transport has made it a promising technology for content-rich wireless multimedia communications. This paper presents a rate-distortion (R-D) optimized packet scheduling algorithm (OPT- MD) for streaming MD-coded video along multiple wireless paths. Our algorithm relies on R-D hint information that is used to characterize a packet in a R-D sense. The information consists of the size of the packet in bits and the importance of the packet for reconstructing the video. Each of the video description adaptively selects certain important packets for transmission according to the quality of the transmission path by simultaneously considering bandwidth, bit error rate, and delay so that the overall end-to-end video distortion in terms of the mean square error (MSE) is minimized. Extensive simulation results demonstrate that OPT-MD can improve the quality of video streaming significantly as compared to a conventional scheduling approach that does not consider the relative importance of the video packets and the channel conditions (RANDOM-MD). The gains in performance reach up to 5 dB and 4 dB for streaming MD-coded format QCIF FORMAN and TABLE video sequences, respectively, in the scenario of adaptation to a simulated time- varying network channel. Our efforts in this work provides an important methodology for high-quality real-time video streaming applications over wireless networks.
An adaptive virtual re-partitioning-based windowing technique for motion compensation

The authors describe a new windowing technique for frames partitioned region-wise or using variable-size blocks, where the virtual repartitioning operation for a given region is carried out adaptively and performed locally. Compared to the existing methods, this technique utilizes more pixels that are in the close neighborhood of the boundaries of the regions in the windowing operation, resulting in a substantial reduction in the prediction error as well as in the blocking effect.
One factorization technique for 2-D digital transfer matrices

The analysis and implementation oi a 2-D digital filter can be considerably simplified when the filter transfer matrix is separable. This simplification can be achieved since the filter is actualiy a cascade connection ot two .l-D filters. Then the analysis and impiementation of the 2-0 filter i§ reduced to those of 1-D filters and the well-established techniques for 1-D filters can be applied. Thus it is of great interest to check if a given 2-D filter is factorizabie into a cascade of two 1-D filters. In thls contribution, we develop a techniouc lor 2-D rational matrix factoriratian. In ~~~ ~~ . ... ~~ ~ ~~ l i l l b d;;ilipmenl we consiaer both singular and nonsingLiar tlansfer matrices. by extendin the conceDt. 01 m h m a i cascaoe seoaration 09 2-D square muwinput multi-butput (MiMO) matrix to the case ot sinoular matrices. Based on this ~~ ~~~~ ~ ~ ~~~ ~~~ technique,^ we <resent a method that can be used to check whether a given 2-D MiMO filter 1s minimay separable into a cascade of two 1-D tilter?..
Fourfold rotational symmetry in two-dimensional functions

The presence of various types of symmetry in the frequency responses of a two-dimensional filter function reflects as constraints on its coefficients. In this paper, such constraints are derived for two-dimensional analog and digital transfer functions so that the magnitude functions of the frequency responses of these transfer functions possess fourfold rotational symmetry. The relationship between fourfold rotational symmetry and quadrantal, diagonal, and octagonal symmetries is also discussed.
An efficient tabu search algorithm for graph bisectioning

A new algorithm for solving the graph bisectioning problem based on tabu search is proposed. The authors run the tabu search algorithm and the Kernighan-Lin algorithm on the same set of random graphs with 50 to 500 nodes and compare their performances. They demonstrate that for all of the graphs their tabu search algorithm provides lower bisection cost than the Kernighan-Lin algorithm; and for all of the graphs with more than 200 nodes, their tabu search algorithm takes less time than the Kernighan-Lin algorithm.<<ETX>>
Wavelet domain-based video noise reduction using temporal discrete cosine transform and hierarchically adapted thresholding

A novel spatio-temporal filter for video denoising, which operates entirely in the wavelet domain, is proposed. For effective noise reduction, the spatial and temporal redundancies that exist in the wavelet domain representation of a video signal are exploited. First, a 2D discrete wavelet transform is applied to the input noisy frames. This is followed by a discrete cosine transform (DCT), which is applied to the temporal subband coefficients to minimise the redundancy among the consecutive frames. The DCT transformed, noise-free coefficients in the different wavelet domain subbands for the original image sequence are modelled using a prior having a generalised Gaussian distribution. On the basis of this prior, filtering of the noisy wavelet coefficients in each subband is carried out using a new, low-complexity wavelet shrinkage method, which utilises the correlation that exists between subsequent resolution levels. Experimental results show that the proposed scheme outperforms several state-of-the-art spatio-temporal filters in terms of both the peak signal-to-noise ratio and the visual quality.
A deterministic direction finding approach using a single snapshot of array measurement

A novel deterministic direction-finding algorithm, which is based on a single snapshot of array measurement, is proposed. A combiner, which applies spatial-domain least-square, is first defined. The power pattern of the combiner output is then generated. The direction-of-arrival of each impinging source corresponds to a main lobe on the power pattern. By searching these main lobes, one can identify the directions-of-arrival of all the sources. Simulation examples are illustrated. The proposed method is simple, and is useful for signal detection in radar, sonar, or seismic detection
A novel technique for tracking time-varying minimum and its applications

A technique for tracking the time-varying minimum of a time-dependent function is proposed. It ensures the tracking process converge exponentially. It also enables the tracking to move from the minimum at one instant of time to the minimum at the next instant of time, without any error. Examples are given to show that this technique is effective for tracking the time-varying minimum. Application of this technique to on-line continuous system identification, on-line neural network learning, etc. gives rise to improved results.
A watermark embedding scheme in wavelet transform domain

In this paper, an efficient watermark embedding scheme is presented in the wavelet transform domain. A pseudorandom sequence is weighted using a weighting function and then embedded to the wavelet transform coefficients of a host image. The proposed new weighting function consists of a perceptual mask and a reliability mask, which take into account, respectively, the imperceptibility and the robustness of the marked image. A detection algorithm based on the correlation of the watermark and the marked image is also proposed. Simulation results show that the proposed embedding algorithm is very robust against various attacks including compression, cropping and low-pass filtering.
Evolutionary design of 2-dimensional recursive filters via the computer language GENETICA

In this paper, we present a new design method for a class of two-dimensional (2-D) recursive digital filters using an evolutionary computational system. The design of the 2-D filter is reduced to a constrained minimization problem the solution of which is achieved by the convergence of an appropriate evolutionary algorithm. In our approach, the genotypes of potential solutions have a uniform probability within the region of the search space specified by the constraints and zero probability outside this region. This approach is particularly effective as the evolutionary search considers only those potential solutions that respect the constraints. We use the computer language GENETICA, which provides the expressive power necessary to get an accurate problem formulation and supports an adjustable evolutionary computational system. Results of this procedure are illustrated by a numerical example, and compared with those of some previous designs.
Feedforward symbol timing recovery technique using two samples per symbol

In this paper, a new feedforward symbol timing recovery technique using timing estimation followed by interpolation is presented for digital receivers with two samples/symbol or higher sampling rate. A few timing estimation algorithms are proposed to estimate the timing offset accurately. The basic algorithm uses only the in-phase (I) or quadrature (Q) signal for timing detection, which applies to a BPSK communication system. It is shown that the basic algorithm, when applied in quadrature modulation systems where both I and Q signals are available, can be modified slightly to yield an improved estimation precision. The mean and variance of the resulting timing estimate are analyzed and simulated, supporting a satisfactory estimation performance. It is also shown that by applying a postprocessing scheme, such as the Kalman filter, the variance can be further reduced, resulting in a smoothed timing estimate. Some of the issues concerning the implementation of the proposed technique are also addressed.
Inference of Gene Regulatory Networks with Variable Time Delay from Time-Series Microarray Data

Regulatory interactions among genes and gene products are dynamic processes and hence modeling these processes is of great interest. Since genes work in a cascade of networks, reconstruction of gene regulatory network (GRN) is a crucial process for a thorough understanding of the underlying biological interactions. We present here an approach based on pairwise correlations and lasso to infer the GRN, taking into account the variable time delays between various genes. The proposed method is applied to both synthetic and real data sets, and the results on synthetic data show that the proposed approach outperforms the current methods. Further, the results using real data are more consistent with the existing knowledge concerning the possible gene interactions.
Rate-optimal static scheduling for DSP data flow graphs onto multiprocessors

This paper is concerned with finding a rate-optimal compile-time (static) scheduling of data flow graphs (DFGs) onto multiprocessor systems. A new analytical approach is proposed to produce a rate-optimal time schedule for a fully specified DFG. In this approach, the DFG is transformed into an acyclic graph through a sequence of circuit contractions. An algorithm to contract a circuit as well as an algorithm to achieve a time scheduling of the given DFG are given. In the scheduling algorithm, the resulting acyclic graph is scheduled followed by a scheduling of the circuits in an order which is reverse to that of their contraction. Further, the issues related to optimizing the schedule in terms of the I/O delay and the number of processors needed, are addressed.
Stability of multidimensional systems using genetic algorithms

The study of the stability of m-dimensional systems is a difficult one especially when m /spl ges/ 3. There exist only a few results in the literature and unfortunately, there does not exist any practical criterion. In this work, the stability of an m-dimensional system is dealt as a minimization problem of the absolute value of its characteristic polynomial over the boundaries of its variables (i.e., on the m unit circles). This minimization problem is solved by using genetic algorithms (GAs). Using GAs we obtain, in general, better results than other methods of minimization (numerical techniques, neural networks, etc.). Numerical examples are presented.
Binary Discrete Cosine and Hartley Transforms

In this paper, a systematic method for developing a binary version of a given transform by using the Walsh-Hadamard transform (WHT) is proposed. The resulting transform approximates the underlying transform very well, while maintaining all the advantages and properties of WHT. The method is successfully applied for developing a binary discrete cosine transform (BDCT) and a binary discrete Hartley transform (BDHT). It is shown that the resulting BDCT corresponds to the well-known sequency-ordered WHT, whereas the BDHT can be considered as a new Hartley-ordered WHT. Specifically, the properties of the proposed Hartley-ordering are discussed and a shift-copy scheme is proposed for a simple and direct generation of the Hartley-ordering functions. For software and hardware implementation purposes, a unified structure for the computation of the WHT, BDCT, and BDHT is proposed by establishing an elegant relationship between the three transform matrices. In addition, a spiral-ordering is proposed to graphically obtain the BDHT from the BDCT and vice versa. The application of these binary transforms in image compression, encryption and spectral analysis clearly shows the ability of the BDCT (BDHT) in approximating the DCT (DHT) very well.
Sparse linear arrays for estimating and tracking DOAs of signals with known waveforms

There are two main ways by which antenna arrays can significantly improve the performance of the direction-of-arrival (DOA) estimation. In the first method, one can extend the array aperture by designing a sparse antennas array. The second method makes use of the temporal information of the received signals, such as the signal waveform. A few articles have dealt with DOA estimation by combining the above two approaches. In this paper, we present a DOA estimation and tracking method by employing the known waveform of the signal and the parallel recursive least square (RLS) technique. When the waveform of the signal is known, the output of each sensor in the array can be considered as a linear regression model of which the coefficients contain the whole information for estimating the DOA. Therefore, the RLS filter is used to estimate and track these coefficients and then the relationship among the coefficients of all the sensors is exploited to obtain the final DOA value without ambiguity. Finally, computer simulation of the proposed method with comparison to the previous methods is conducted.
A homomorphic system to reduce speckle in videos

In this paper, we propose an unbiased homomorphic system to reduce speckle in videos. The speckle is modeled as a multiplicative noise having a lognormal distribution. In the proposed homomorphic system, first, the natural logarithm function is applied on the corrupted signal to transform the multiplicative nature of the noise into an additive one. Then, a spatial filter is applied to the signal obtained after the transformation. This is followed by the application of a temporal filter, which uses a change detection technique to measure the interframe motion, to the output of the spatial filter. The spatial estimate obtained from the spatial filter and the spatiotemporal estimate at the output of the temporal filter are then combined in a suitable way to get an intermediate signal. Exponentiation is then applied to this intermediate signal to get an estimate of the original signal. Then a technique to compensate for the biasing that occurs within the homomorphic system is applied to the output of the system in order to get an unbiased estimate of the original signal. The quantitative and the qualitative performance of the proposed system are studied and compared with that of the two existing schemes. It is found that the proposed filters have much less processing time and also perform better noise reduction compared to the other two.
Joint noise distribution parameter estimation and LDPC decoding using variational Bayes

In this work, we investigate the problem of estimating time-varying noise distribution parameter on a factor graph. A new message passing scheme is proposed by incorporating the variational Bayes (VB) into the belief propagation algorithm for estimating of time-varying noise distribution parameter in a low-density parity-check decoder. The scheme can also be used for the estimation of the correlation noise model parameter in distributed video coding. A Bayesian estimator is used to estimate this parameter by obtaining its posterior distribution given the channel output. The VB algorithm is employed to approximate the complex form of the posterior distribution with a simple distribution. Finally, this distribution is used to derive a closed-form expression for the messages on the augmented factor graph for online parameter estimation and decoding process at the same time.
Design of circularly symmetric two-dimensional FIR digital filters employing transformations with variable parameters

A modification of the trasformation method used for the design of two-dimensional (2-D) circularly symmetric finite impulse response (FIR) digital filters from one-dimensional (1-D) filters is described. This modification entails the embedding of variable parameters in the different transformations applied to the different factors of the 1-D reference function. This new method results in the design of 2-D FIR filters whose frequency response characteristics meet the cutoff boundary specifications more closely than the transformations without the modification. This method is quite useful for the design of 2-D FIR filters with multiple cutoff boundaries such as bandpass filters.
Design of weighted order statistic filters using linearly separable stack-like architecture

This paper introduces a novel procedure for the design of weighted order statistic filters which are approximately optimal in the mean absolute error sense, for estimating a signal from a noise-corrupted observation of the same. In the proposed procedure, the design is carried out by using a new type of filter architecture designated as a linearly separable stack-like filter. An application for restoring images corrupted by impulsive noise is considered.
A binary logic synthesis approach to the bit-level implementation of generalized rank-order filters

A binary logic synthesis approach is presented for the bit-level implementation of generalized rank-order filters. It is shown that rank-order filters can be realized directly from the binary weighted signal by using combinational logic circuits. A pipelined architecture based on the algorithm is also introduced. The realization is simple and modular in structure and suitable for VLSI implementation, and no threshold decomposition and reconstruction circuits are needed. Only one type of basic cell is employed. K basic cells connected together will perform K-bit rank-order filtering. The proposed filter has flexibility for various applications. Considering the proposed architecture as a building block, recursive rank-order filters, 2-D rank-order filters, and adaptive rank-order filters can easily be realized.<<ETX>>
Neighbourhood-blocks motion vector estimation technique using pyramidal data structure

A pyramidal motion estimation technique that makes use of the motion correlation within a pyramidal level is proposed. In the proposed technique, motion vectors from neighbouring motion blocks are taken into consideration as possible candidates. This is done in lieu of scaling the motion vectors from the corresponding positions at the adjacent lower pyramidal level as the prediction motion vectors for the current pyramidal level (as performed in the conventional technique). Each of these candidate motion vectors is used as the prediction motion vector and refined, and the one that has the least matching distortion is chosen as the motion vector at the current pyramidal level. Compared to the conventional pyramidal motion estimation technique, the proposed method effectively overcomes the problem of propagation of false motion vectors. Simulation studies show that a substantial improvement is achieved in the performance, both in terms of the prediction mean square error and the number of coding bits for the motion vectors.
A least-square solution to the design problem of 2-D linear-phase FIR filters with arbitrary magnitude responses

In this paper, we present a least-square design algorithm for general 2-D linear-phase FIR filters and obtain a novel closed-form solution for filter coefficients. This solution is derived for the approximation of arbitrarily shaped magnitude responses and is given as an explicit expression in the desired magnitude specifications, making it possible to evaluate very fast the impulse response of the designed filter. It is shown that a further computational reduction can be achieved when this solution is used to design those filters which have centro-symmetric or quadrantally symmetric magnitude responses.