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2009 International Conference on Image processing, computer Vision, and Pattern Recognition, IPCV 2009

作者： Lahlou, Mouncef Adjouadi, Malek Barreto, Armando Center for Advanced Technology and Education Department of Electrical and Computer Engineering Florida International University Miami FL United States Digital Signal Processing Laboratory Department of Electrical and Computer Engineering Florida International University Miami FL United States

ISBN: (纸本)9781601321190

Detecting faces accurately under natural lighting conditions remains a challenging task for advancing the performance of face recognition systems. Most face detection algorithms are associated with visible spectrum imagery which compromises their efficiency when image acquisition is subject to variable illumination. In this study, we propose a simple yet powerful solution that uses multiple cues to detect and locate faces accurately in near infrared (NIR) imaging systems. Specific objectives include (I) extract optimally the illumination and reflectance components of the original image using an intrinsic images decomposition technique, (2) modify the segmentation process by using an energy minimization procedure in an adaptive fashion, and (3) propose an enhanced face detection process on the basis of pupil localization. The evaluation of our face detector on image sequences of 45 different subjects from the CBSR NIR face dataset demonstrated a highly competitive accuracy with less than 5% error rate.

关键词： Face recognition

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A new improved model-based seizure detection using statistically optimal null filter

A new improved model-based seizure detection using statistic...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Rajeev Yadav R. Agarwal M. N.S. Swamy Center of Signal Processing and Communications (CENSIPCOM) Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

A patient-specific model-based seizure detection method using statistically optimal null filters (SONF) has been recently proposed to aid the review of long-term EEG [1, 2]. The method relies on the model of a priori known seizure (template pattern) for subsequent detection of similar seizures. Artifacts, non-epileptic EEG rhythms, and at times modeling errors lead to increased false or missed detections. In this paper, we present a new improved model-based seizure detection that introduces a pre-processing block for artifact rejection, an adaptive technique of modeling the template patterns, and a new evolution-based classifier. The proposed classifier tracks the temporal evolution of seizure to improve the classification accuracy. With the help of simulated EEG, we illustrate the significance and need for these modifications. Further, performance of the complete algorithm is tested on single channel depth EEG of seven patients, and compared with the previous approaches. In terms of sensitivity and specificity, the proposed method resulted in 84% and 100%, method of 65% and 84%, and method of, 84% and 90% respectively. An overall performance improvement is seen as enhanced detection sensitivity and reduced false positives. This is preliminary result on seven patient data.

关键词： Electroencephalography Brain modeling Rhythm Filters Monitoring Epilepsy Sampling methods Frequency USA Councils Testing

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On the Convergence of Perturbed Non-Stationary Consensus Algorithms

On the Convergence of Perturbed Non-Stationary Consensus Alg...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and communications Societies

作者： T. C. Aysal K. E. Barner Communications Research in Signal Processing Group School of Electrical and Computer Engineering Cornell University Ithaca NY USA Signal Processing and Communications Group Electrical and Computer Engineering Department University of Delaware Newark DE USA

ISBN: (纸本)9781424435128

We consider consensus algorithms in their most general setting and provide conditions under which such algorithms are guaranteed to converge, almost surely, to a consensus. Let {A(t),B(t)} isin R N times N be (possibly) random, non-stationary matrices and {x(t),m(t)} isin R N times 1 be state and perturbation vectors, respectively. For any consensus algorithm of the form x(t + 1) = A(t)x(t) + B(t)m(t), we provide conditions under which consensus is achieved almost surely, i.e., Pr {lim trarrinfin x(t) = c1} = 1 for some c isin R. Moreover, we show that this general result subsumes recently reported results for specific consensus algorithms classes, including sum-preserving, non-sum-preserving, quantized and noisy gossip algorithms. Also provided are the e-converging time for any such converging iterative algorithm, i.e., the earliest time at which the vector x(t) is e close to consensus, and sufficient conditions for convergence in expectation to the initial node measurements average.

关键词： Convergence signal processing algorithms Iterative algorithms Peer to peer computing Computational modeling communications Society Sufficient conditions Time measurement Ad hoc networks Application software

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Perturbation analysis of whitening-rotation-based semi-blind MIMO channel estimation

Perturbation analysis of whitening-rotation-based semi-blind...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Feng Wan Wei-Ping Zhu M.N.S. Swamy Centre of Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

The whitening-rotation (WR)-based semi-blind methods have been shown to achieve much better channel estimation performance than the conventional training-based methods for MIMO systems. In this paper, the performance analysis is conducted for an ideal WR-based method, in which the knowledge of the ideal whitening matrix is known a priori. This analysis is a valuable study since the ideal WR-based method provides the upper bound of the channel estimation performance for WR-based methods. First, the expression of the error of the rotation matrix is derived by using a perturbation analysis. This result is then utilized to derive a closed-form expression of mean square error (MSE) of the ideal WR-based method. The simulation studies have shown that the theoretical MSE values are consistent with the simulation results, confirming the high accuracy of the derivation of the MSE expression.

关键词： MIMO Channel estimation Receiving antennas signal processing algorithms Performance analysis Mean square error methods Maximum likelihood estimation Transmitting antennas signal processing Upper bound

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A semi-blind algorithm for most significant tap detection in channel estimation of OFDM systems

A semi-blind algorithm for most significant tap detection in...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Feng Wan Wei-Ping Zhu M.N.S. Swamy Centre of Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

ISBN: (纸本)9781424438273

In this paper, a semi-blind algorithm is proposed for the detection of most significant tap (MST) in the sparse channel estimation of OFDM systems. Based on an analysis of the second-order statistics of the signal received through a noise-free sparse channel, a direct relationship between the positions of the most significant taps (MST) of the sparse channel and the lags of the nonzero correlation functions is revealled, leading to an efficient semi-blind MST detection algorithm. By using the acquired MST position, a sparse least square channel estimate is then obtained. A number of computer simulation-based experiments are carried out to confirm the effectiveness of the proposed semi-blind MST detection algorithm and the associated sparse LS channel estimation method.

关键词： Channel estimation OFDM signal processing algorithms Delay estimation Detection algorithms signal analysis Algorithm design and analysis Statistical analysis Delay lines Least squares approximation

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A spectral matching method for pitch estimation from noise-corrupted speech

A spectral matching method for pitch estimation from noise-c...

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IEEE International Symposium on Circuits and Systems (ISCAS)

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

ISBN: (纸本)9781424438273

An effective method for pitch estimation from severely noise-corrupted speech is presented in this paper. We argue that an accurate estimate of a pitch-harmonic (PH) can be obtained from the Discrete Cosine Transform (DCT) power spectrum of an enhanced frame. By exploiting the PH thus extracted, a spectral matching method is developed in the DCT domain to determine the true harmonic number associated to the PH that leads to a pitch estimate. In a heavy noisy scenario, the superior efficacy of the proposed pitch estimation method relative to some of the existing ones is confirmed through simulation results using the Keele database.

关键词： Speech enhancement Discrete cosine transforms Noise reduction Speech coding Speech synthesis Noise robustness Autocorrelation White noise Additive noise Low pass filters

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A time-frequency domain formant frequency estimation scheme for noisy speech signals

A time-frequency domain formant frequency estimation scheme ...

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IEEE International Symposium on Circuits and Systems (ISCAS)

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

ISBN: (纸本)9781424438273

Formant frequency is a one of the most important speech feature, which has widespread applications in speech recognition, synthesis, and compression. In this paper, a new time-frequency domain scheme for the estimation of formant frequencies from noise-corrupted speech signals is presented. In order to overcome the adverse effect of noise, instead of conventional autocorrelation function (ACF), a repeated ACF (RACF) of the noisy speech is employed. Exploiting the characteristics of the zero lag, a set of equations containing the lower lags of the RACF of the noisy speech is used to estimate the formant frequencies. In order to avoid estimation errors that may occur in the case of weak formants, a frequency-domain algorithm is introduced utilizing the RACF of the observed speech. Formant frequency estimation accuracy is measured for different natural and synthetic vowels in noisy environments and even at low levels of signal-to-noise ratio, a better performance is obtained by the proposed scheme in comparison to some of the existing methods.

关键词： Time frequency analysis Frequency estimation Speech synthesis Working environment noise signal to noise ratio Frequency synthesizers Speech recognition signal synthesis Autocorrelation Speech enhancement

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Iteratively detected MIMO-OFDM twisted-pair transmission schemes

Iteratively detected MIMO-OFDM twisted-pair transmission sch...

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作者： Ahrens, Andreas Lange, Christoph Department of Electrical Engineering Computer Science Communications Signal Processing Group University of Technology Philipp-Müller-Straße 14 23966 Wismar Germany T-Systems Enterprise Services GmbH Goslarer Ufer 35 Berlin 10589 Germany

ISBN: (纸本)9783642051968

Crosstalk between neighbouring wire pairs in multi-pair copper cables is an important disturbance, which essentially limits the transmission quality and the throughput of such cables. For high-rate transmission, often the strong near-end crosstalk (NEXT) disturbance is avoided or suppressed and only the far-end crosstalk (FEXT) remains as crosstalk influence. In this contribution the FEXT impact in iteratively detected MIMO-OFDM transmission schemes is studied. Extrinsic information transfer (EXIT) charts are used for analyzing and optimizing the convergence behaviour of the iterative demapping and decoding. Our results show that FEXT is not necessarily a limiting factor if appropriate signal processing strategies are used. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Orthogonal frequency division multiplexing

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Spectral derivative feature coding for hyperspectral signature analysis

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Pattern Recognition 2009年第3期42卷 395-408页

作者： Chang, Chein-I Chakravarty, Sumit Chen, Hsian-Min Ouyang, Yen-Chieh Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Environmental Restoration and Disaster Reduction Research Center National Chung Hsing University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Department of Radiology China Medical University Hospital Taichung Taiwan

This paper presents a new approach to hyperspectral signature analysis, called spectral derivative feature coding (SDFC). It is derived from texture features used in texture classification to dictate gradient changes among adjacent bands in characterizing spectral variations so as to improve better spectral discrimination and classification. In order to evaluate its performance, two known binary coding methods, spectral analysis manager (SPAM) and spectral feature-based binary coding (SFBC) are used to conduct comparative analysis. Experimental results demonstrate that the proposed SDFC performs more effectively in capturing spectral characteristics than do SPAM and SFBC. © 2008 Elsevier Ltd. All rights reserved.

关键词： Spectrum analysis

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Whitening-rotation-based semi-blind estimation of MIMO FIR channels

Whitening-rotation-based semi-blind estimation of MIMO FIR c...

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International Conference on Wireless communications and signal processing (WCSP)

作者： Qingwu Zhang Wei-Ping Zhu Qingmin Meng Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications Nanjing China Centre of Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

In this paper, a new semi-blind algorithm is presented for the estimation of Multiple-Input Multiple-Output (MIMO) Finite Impulse Response (FIR) channels. First, by using the MIMO linear prediction (LP), the whitening matrix is estimated blindly from the received data. The rotation matrix is then estimated by employing pilot symbols. The proposed method is validated through computer simulation-based experimentations, showing a high estimation accuracy as compared to the LS method in terms of the MSE of the channel estimate.

关键词： MIMO Finite impulse response filter Channel estimation signal processing algorithms Receiving antennas Matrix decomposition Maximum likelihood estimation Telecommunication computing Computational modeling computer simulation

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