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An Algorithm for ARMA Model Parameter Estimation from Noisy Observations

An Algorithm for ARMA Model Parameter Estimation from Noisy ...

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2008 IEEE International Symposium on Circuits and Systems (ISCAS 2008), vol.9

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

This paper presents a new algorithm for the parameter estimation of minimum-phase autoregressive moving average (ARMA) systems from noise-corrupted observations. In order to estimate the AR parameters of the ARMA system, based on a repeated autocorrelation function (ACF) of the observed data, a set of zero lag compensated equations has been developed. For the estimation of the MA parameters, first, a noise-subtraction algorithm is proposed to reduce the effect of noise from the ACF of the residual signal which is obtained by filtering the noisy ARMA signal via the estimated AR parameters. The MA parameters are then estimated by using a spectral factorization corresponding to the noise-compensated ACF of the residual signal. computer simulations are carried out for ARMA systems of different orders under noisy environments and simulation results demonstrate a superior identification performance in terms of estimation accuracy and consistency.

关键词： Parameter estimation Working environment noise signal processing algorithms Noise reduction Autoregressive processes Autocorrelation Equations signal processing computer simulation Filters

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A signal Perturbation Free Transmit Scheme for MIMO Channel Estimation

A Signal Perturbation Free Transmit Scheme for MIMO Channel ...

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IEEE Conference on Vehicular Technology (VTC)

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

In this paper, a novel signal perturbation free transmit scheme is proposed for MIMO channel estimation. A perturbation analysis of the WR-based method is first conducted, showing that the method is subject to a signal perturbation error and therefore, its performance is very poor under the moderate to high signal-to-noise ratios (SNRs). A new transmit structure is then proposed to cancel the signal perturbation error at the receiver in order to improve the performance of the WR-based method in the high SNR case. computer simulations show that the WR-based method with the proposed signal perturbation free transmit scheme significantly outperforms the original WR-based method as well as the training-based LS method in terms of the MSE of the channel estimate.

关键词： MIMO Channel estimation signal to noise ratio Noise Algorithm design and analysis Matrix decomposition Receiving antennas

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On the estimation of pitch of noisy speech based on time and frequency domain representations

On the estimation of pitch of noisy speech based on time and...

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Canadian Conference on electrical and computer engineering (CCECE)

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

In this paper, we propose a new algorithm for pitch estimation from speech signals heavily degraded by additive noise based on both time and frequency domain representations. A least-squares minimization technique is first developed for the accurate estimation of a pitch-harmonic (PH) wherein a harmonic sinusoidal model of clean speech is exploited as a time domain representation. Then, relying on a power spectrum in the Fast Fourier Transform domain which is a frequency domain representation, a two-step criterion is formulated in order to acquire a true harmonic number corresponding to the extracted PH for robust pitch detection. Extensive simulations have been carried out to demonstrate the effectiveness of the proposed methodology as compared to some of the existing techniques in literature. It has been shown that our new approach consistently outperforms the other methods especially at low levels of signal-to-noise ratio (SNR).

关键词： Frequency estimation Frequency domain analysis Speech enhancement Fast Fourier transforms signal processing algorithms Additive noise signal to noise ratio Personal digital assistants Autocorrelation Noise robustness

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Evaluation of voice activity and voicing detection

Evaluation of voice activity and voicing detection

引用

INTERSPEECH 2008 - 9th Annual Conference of the International Speech Communication Association

作者： Kotnik, Bojan Sendorek, Pierre Astrov, Sergey Koc, Turgay Ciloglu, Tolga Fernández, Laura Docío Banga, Eduardo Rodríguez Höge, Harald Kačič, Zdravko Faculty of Electrical Engineering and Computer Science University of Maribor Slovenia Department TSI Signal-Images Telecom Paristech France Corporate Technology Siemens AG Munich Germany Electrical and Electronics Eng. Dept Middle East Technical University Ankara Turkey Signal Processing and Communications Dept. University of Vigo Spain

This paper describes the ECESS evaluation campaign of voice activity and voicing detection. Standard VAD classifies signal into speech and non-speech, we extend it to VAD+ so that it classifies a signal as a sequence of non-speech, voiced and unvoiced segments. The evaluation is performed on a portion of the Spanish SPEECON database with manually labeled segmentation. To avoid errors caused by the limited precision of manual labeling we introduce "dead zones" -tolerance intervals ±5 ms around label changes in the data set. In these tolerance intervals we don't evaluate the signal. Copyright © 2008 ISCA.

关键词： Speech communication

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Fast Blind Adaptive Channel Shortening Using signal Subspace

Fast Blind Adaptive Channel Shortening Using Signal Subspace

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IEEE Conference on Vehicular Technology (VTC)

作者： Mahdi Karami Ali Olfat Signal Processing & Communication Systems Laboratory Department of Electrical and Computer Engineering University of Tehran Iran

In cyclic-prefixed communication systems, if the delay spread of the channel is longer than the cyclic prefix (CP) a channel-shortening equalizer (CSE) can be used to restore the desired operation of such systems. Since in time-varying environment we are interested in fast adaptive equalizer with tracking capability, the aim of this paper is to propose RLS-type algorithm for channel shortening. In this paper, we first propose an RLS-type algorithm to estimate the eigenvector corresponding to the smallest eigenvalue of a matrix and based on this algorithm we develop an RLS-type blind channel shortener. We also, based on PAST algorithm, propose an RLS-type update rule to shorten the channel under MMSE criterion. Simulations show the speed advantage of the proposed algorithms.

关键词： signal processing algorithms OFDM Nonlinear filters Equalizers Eigenvalues and eigenfunctions Finite impulse response filter signal processing Adaptive signal processing Laboratories Delay systems

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Efficient Riemannian algorithms for optimization under unitary matrix constraint

Efficient Riemannian algorithms for optimization under unita...

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

作者： Traian Abrudan Jan Eriksson Visa Koivunen Department of Electrical and Communications Engineering SMARAD CoE Signal Processing Laboratory Helsinki University of Technology HUT Finland

In this paper we propose practical algorithms for optimization under unitary matrix constraint. This type of constrained optimization is needed in many signal processing applications. Steepest descent and conjugate gradient algorithms on the Lie group of unitary matrices are introduced. They exploit the Lie group properties in order to reduce the computational cost. Simulation examples on signal separation in MIMO systems demonstrate the fast convergence and the ability to satisfy the constraint with high fidelity.

关键词： Constraint optimization signal processing algorithms Array signal processing Source separation MIMO Computational modeling Convergence Subspace constraints Independent component analysis Matrix converters

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Joint angle tracking with inertial sensors

Joint angle tracking with inertial sensors

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

作者： Mahmoud El-Gohary Sean Pearson James McNames Department of Electrical and Computer Engineering Biomedical Signal Processing Laboratory Portland State University Portland OR USA

Many wearable inertial systems have been used to continuously track human movement in and outside of a laboratory. The number of sensors and the complexity of the algorithms used to measure position and orientation vary according to the clinical application. To calculate changes in orientation, researchers often integrate the angular velocity. However, a relatively small error in measured angular velocity leads to large integration errors. This restricts the time of accurate measurement to a few minutes. We have combined kinematic models designed for control of robotic arms with state space methods to directly and continuously estimate the joint angles from inertial sensors. These algorithms can be applied to any combination of sensors, can easily handle malfunctions or the loss of some sensor inputs, and can be used in either a real-time or an off-line processing mode with higher accuracy.

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A pyramid-based block of skewers for pixel purity index for endmember extraction in hyperspectral imagery

A pyramid-based block of skewers for pixel purity index for ...

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作者： Chang, Chein-I Hsueh, Mingkai Liu, Weimin Wu, Chao-Cheng Chaudhry, Farzeen Solyar, Gregory Plaza, Antonio Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States Computer Science Department University of Extremadura Avda. de la Universidad s/n 10.071 Caceres Spain

Pixel Purity Index (PPI) has been widely used for endmember extraction. Recently, an approach using blocks of skewers was proposed by Theiler et al., called blocks of skewers (BOS) method, to improve computation of the PPI. It utilizes a block of skewers to reduce number of calculations of dot products operated by the PPI on each skewers with all data sample vectors. Unfortunately, the BOS method also suffers from the same drawbacks that the PPI does in terms of several parameters which are needed to be determined a priori. Besides, it also has an additional parameter, block size, B needed to be determined where no guideline is provided of how to select this parameter. In this paper, the BOS method is also investigated. Most importantly, a new pyramid-based block design for the BOS method is also introduced as opposed to the cube-based block designed used by Theiler et al.'s BOS. One major advantage of our proposed pyramid-based BOS over Theiler et al.'s cube-design BOS is the hardware design for Field Programmable Gate Arrays (FPGAs) implementation. © 2008 World Scientific Publishing Company.

关键词： Pixels

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Blind Source Separation Based on Generalised Canonical Correlation Analysis and Its Adaptive Realization

Blind Source Separation Based on Generalised Canonical Corre...

引用

Congress on Image and signal processing, CISP

作者： Wei Liu Danilo P. Mandic Andrzej Cichocki Communications Research GroupDepartment of Electronic & Electrical Engineering University of Sheffield UK Department of Electrical & Electronic Engineering Imperial College London Communications and Signal Processing Research Group UK RIKEN Laboratory for Advanced Brain Signal Processing Brain Science Institute Japan

The canonical correlation analysis (CCA) approach is generalised to accommodate the case with added white noise. It is then applied to the blind source separation (BSS) problem for noisy mixtures. An adaptive blind source extraction algorithm is derived based on this idea. A proof is provided that by this generalised CCA approach, the source signals can be recovered successfully, which is also supported by simulation results.

关键词： Blind source separation Source separation signal processing algorithms Covariance matrix Autocorrelation Adaptive signal processing White noise Image analysis signal analysis Degradation

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Speech enhancement using a Kalman-based normalized LMS algorithm

Speech enhancement using a Kalman-based normalized LMS algor...

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International Symposium on Telecommunications, IST

作者： A. Mahmoodzadeh H. R. Abutalebi H. Agahi Signal Processing Research Laboratory Electrical Engineering Department Yazd University Yazd Iran Electrical and Computer Engineering Department University of Tehran Tehran Iran

This paper deals with the problem of Adaptive Noise Cancellation (ANC) for the speech signal corrupted with an additive white Gaussian noise. After explaining the least Mean Square (LMS)-based adaptive filter and Kalman filter, we examine the hybrid Kalman-based LMS (KLMS) technique for adaptation of the ANC. The proposed technique suggests a way to normalize LMS algorithm using Kalman filter. Our simulation shows that the KLMS method converges faster and is more stable compared to the LMS and its Normalized version, NLMS.

关键词： Artificial neural networks Least squares approximation Kalman filters Speech Speech enhancement Adaptive filters Noise

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