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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： S.A. Fattah W.-P. Zhu M.O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

A new approach for the identification of minimum-phase autoregressive moving average (ARMA) systems in the presence of heavy noise is presented in this paper. A damped sinusoidal (DS) model for the autocorrelation function of a noise-free ARMA signal is proposed to estimate the AR parameters, which overcomes the failure of conventional correlation based techniques in estimating the AR parameters of an ARMA system at a very low signal-to-noise ratio (SNR). The MA parameters of the ARMA system are then estimated by using Durbin's method along with an optimum order selection criterion. Both white noise and periodic impulse train excitations are considered for the application of the proposed method to system identification as well as to speech processing. computer simulations are carried out based on both synthetic ARMA systems and natural speech signals, showing superior identification results even at an SNR of -5 dB for which most of the existing methods would fail.

关键词： System identification signal to noise ratio Parameter estimation Autoregressive processes Autocorrelation White noise Application software Speech processing computer simulation Natural languages

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A subspace constrained constant modulus algorithm for blind array

A subspace constrained constant modulus algorithm for blind ...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Y.X. Chen W.-P. Zhu M.N.S. Swamy Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

It is known that the stochastic gradient descent (SGD)-based constant modulus algorithm (CMA) has the drawback of slow convergence rate. It is also known that under some weak conditions, all local minima of CMA are identical to that of a CMA which is constrained in signal subspace. Based on this property, we propose a subspace-constrained CMA that is able to increase the convergence rate of the conventional SGD-CMA. To reduce the computational complexity, a technique referred to as projection approximate subspace tracking with deflation (PASTd) is used to calculate the signal subspace. Our simulation shows that the proposed algorithm is significantly superior to the conventional SGD-CMA both in the convergence rate and in the sensitivity to the step size.

关键词： Subspace constraints signal processing algorithms Array signal processing Cost function Stochastic processes Convergence Computational modeling Covariance matrix Estimation error Directive antennas

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Noisy autoregressive system identification by the ramp cepstrum of one-sided autocorrelation function

Noisy autoregressive system identification by the ramp cepst...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： S.A. Fattah W.-P. Zhu A.O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

The paper presents a new approach for the identification of minimum-phase autoregressive (AR) systems in the presence of heavy noise. A damped cosine model for the ramp cepstrum of the one-sided autocorrelation function of a noise-free AR signal is proposed to estimate the AR parameters. The AR parameters are obtained directly from the estimated damped cosine model parameters. The proposed method overcomes the failure of conventional cepstrum and correlation based techniques in noisy AR system identification at a very low signal-to-noise ratio (SNR). computer simulations are carried out based on. both synthetic AR systems and natural speech signals, showing superior identification results even at an SNR of -5 dB for which most of the existing methods would fail.

关键词： System identification Cepstrum Autocorrelation Parameter estimation signal to noise ratio Working environment noise Biomedical signal processing signal processing Speech processing Equations

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A robust pitch estimation approach for colored noise-corrupted speech

A robust pitch estimation approach for colored noise-corrupt...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： C. Shahnaz W.-P. Zhu M.O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

We present an integrated pitch estimation approach for severely colored noise-corrupted speech. An effective colored noise-whitening process is first applied to the noisy speech. Then, a variable-length average magnitude difference function (VLAMDF) of the pre-filtered noisy speech (PFNS) is proposed, which almost conquers the trend of falling valleys in the conventional AMDF. The amplitude characteristic of the VLAMDF is reshaped by means of a simple linear transformation to reduce the possibility of double-pitch-errors. As the VLAMDF exhibits a valley while the autocorrelation function (ACF) of PFNS provides a peak, the ACF is weighted by the reciprocal of the VLAMDF to emphasize the pitch-candidate as well as to suppress the non-pitch peaks. Moreover, a noise-robust pitch detection in the time-domain is guaranteed by collaboration of this enhanced autocorrelation function with the reshaped version of the VLAMDF. The proposed approach is simulated using the Keele reference database and provides a superior accuracy relative to some of the existing methods implemented in the presence of colored noise, even at a very low signal-to noise ratio (SNR) of -15 dB.

关键词： Noise robustness Colored noise Autocorrelation Speech processing signal to noise ratio Speech coding Speech synthesis Working environment noise Additive noise signal processing

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MAC protocols for optimal information retrieval pattern in sensor networks with mobile access

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Eurasip Journal on Wireless communications and Networking 2005年第4期2005卷 493-504页

作者： Yang, Zhiyu Dong, Min Tong, Lang Sadler, Brian M. School of Electrical and Computer Engineering Cornell University Ithaca NY 14853 United States Corporate Research and Development QUALCOMM Incorporated 5775 Morehouse Drive San Diego CA 92121 United States Army Research Laboratory Adelphi MD 20783-1197 United States School of Electrical and Computer Engineering Cornell University Ithaca NY Cooperate Research and Development QUALCOMM Incorporated San Diego CA United States Adelphi MD United States IEEE Technical Committee on Signal Processing for Communications

In signal field reconstruction applications of sensor network, the locations where the measurements are retrieved from affect the reconstruction performance. In this paper, we consider the design of medium access control (MAC) protocols in sensor networks with mobile access for the desirable information retrieval pattern to minimize the reconstruction distortion. Taking both performance and implementation complexity into consideration, besides the optimal centralized scheduler, we propose three decentralized MAC protocols, namely, decentralized scheduling through carrier sensing, Aloha scheduling, and adaptive Aloha scheduling. Design parameters for the proposed protocols are optimized. Finally, performance comparison among these protocols is provided via simulations.

关键词： Wireless telecommunication systems

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OFDM performance analysis in the presence of synchronization errors induced by hot carriers

OFDM performance analysis in the presence of synchronization...

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IEEE Conference on Vehicular Technology (VTC)

作者： S.R. Herlekar Hsiao-Chun Wu Chi Zhang A. Srivastava Communications and Signal Processing Laboratory and VLSI Circuit Design Laboratory Department of Electrical & Computer Engineering Louisiana State University Baton Rouge LA USA

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Characterization of a cascade LMS predictor

Characterization of a cascade LMS predictor

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2005 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP '05

作者： Huang, D.Y. Su, X. Nallanathan, A. Multimedia Signal Processing Laboratory Media Division Institute for Infocomm Research 21 Heng Mui Keng Terrace Singapore 119613 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore 119260 Singapore

ISBN: (纸本)0780388747

In this paper, an FIR cascade structure for adaptive linear prediction is studied in which each stage FIR filter is independently adapted using LMS algorithm. The theoretical analysis shows that the cascade performs a linear prediction in a way of successive refinement and each stage tries to obliterate the dominant mode of its input. Experimental results show that the performance of the cascade LMS predictor are in good agreement with our theoretical analysis. ©2005 IEEE.

关键词： signal filtering and prediction

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A VLSI architecture for a high-speed computation of the 1D discrete wavelet transform

A VLSI architecture for a high-speed computation of the 1D d...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Chengjun Zhang Chunyan Wang M.O. Ahmad Center for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University West Montreal QUE Canada

An efficient VLSI architecture for the computation of the convolution-based discrete wavelet transform (DWT) is presented. The proposed architecture, employing two processing elements and a single buffer in a pipeline mode, enhances the processing time by appropriately decomposing the overall computations and distributing them equally between the two processing elements. The data flow, both within and between the processing elements, is streamlined, making use of the buffer and employing multiple input data paths within the processing elements. The parallelism of operations carried out by the computational blocks in each processing element is made more effective by equalizing the data paths used in these blocks. HSPICE and Verilog simulation results are presented to show that a circuit, whose design is based on the proposed architecture, is, in comparison with other existing architectures, fast and efficient for DWT computation, with a modest decrease in the area.

关键词： Discrete wavelet transforms Very large scale integration computer architecture Pipelines Distributed computing Parallel processing Concurrent computing Hardware design languages Computational modeling Circuit simulation

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Feature selection: We've barely scratched the surface

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IEEE INTELLIGENT SYSTEMS 2005年第6期20卷 74-76页

作者： Forman, G Hewlett-Packard Labs. United States Arizona State University United States Department of Electrical Engineering United States Genomic Signal Processing Laboratory Texas A and M University United States Computational Biology Division Translational Genomics Resesarch Insititute Phoenix United States Department of Electrical and Computer Engineering Northeastern University United States Motorola Labs. Intel Genomics Division Lawrence Berkeley National Laboratory United States Lawrence Berkeley National Laboratory United States Life Science Division Lawrence Berkeley National Laboratory United States Neurogenomics Division Translational Genomics Research Institute United States Department of Computer Science and Engineering Fulton School of Engineering Arizona State University United States Department of Computer Science University of New York Binghamton United States Department of Computer Science and Engineering Arizona State University United States

Various feature selection techniques were studied. The trend toward richer data types is pushing feature selection in both scale and complexity. Natural language text features and image features are becoming commonplace. Several trends will increase the demand for feature selection. Time plays an additional role in some nonstationary domains where the best features have a seasonal dependency.

关键词： Feature extraction

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Design of fast algorithms for pixel purity index for endmember extraction in hyperspectral imagery

Design of fast algorithms for pixel purity index for endmemb...

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Annual Conference 2005 - Geospatial Goes Global: From Your Neighborhood to the Whole Planet

作者： Chaudhry, Farzeen Chakravarty, Sumit Plaza, Antonio Chang, Chein-I. Department of Computer Science and Electrical Engineering Remote Sensing Signal and Image Processing Laboratory University of Maryland Baltimore MD 21250 United States Computer Science Department University of Extremadura Avda. de la Universidad s/n 10.071 Caceres Spain

ISBN: (纸本)1570830762

This paper presents new fast algorithms to improve the widely used endmember extraction algorithm, called pixel purity index (PPI) and also modify a revised version of PPI, called block of skewers (BOS) method. Since both the PPI and the BOS method suffer from same drawbacks in implementation, our proposed algorithms are designed to mitigate these dilemmas by introducing a newly developed concept, called virtual dimensionality (VD) and a process that can automatically determine a set of endmembers without appealing for parameters used in the PPI and BOS method. As a result, two modified PPI and BOSPPI algorithms are developed. Unlike the PPI and BOS method, the two new algorithms are iterative and provide stopping rules to automatically extract endmembers without manually selecting endmembers. The experimental study shows that the MPPI performs better than the PPI not only in computational complexity, but also in stability and performance, and the MBOSPPI could perform better than the BOS method if the blocks of skewers are properly designed. © 2005 by the American Society for Photogrammetry and Remote Sensing.

关键词： Iterative methods

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