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71
Independent Component Analysis
 Neural Computing Surveys
, 2001
"... A common problem encountered in such disciplines as statistics, data analysis, signal processing, and neural network research, is nding a suitable representation of multivariate data. For computational and conceptual simplicity, such a representation is often sought as a linear transformation of the ..."
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Cited by 1697 (98 self)
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A common problem encountered in such disciplines as statistics, data analysis, signal processing, and neural network research, is nding a suitable representation of multivariate data. For computational and conceptual simplicity, such a representation is often sought as a linear transformation of the original data. Wellknown linear transformation methods include, for example, principal component analysis, factor analysis, and projection pursuit. A recently developed linear transformation method is independent component analysis (ICA), in which the desired representation is the one that minimizes the statistical dependence of the components of the representation. Such a representation seems to capture the essential structure of the data in many applications. In this paper, we survey the existing theory and methods for ICA. 1
Multichannel Blind Deconvolution: Fir Matrix Algebra And Separation Of Multipath Mixtures
, 1996
"... A general tool for multichannel and multipath problems is given in FIR matrix algebra. With Finite Impulse Response (FIR) filters (or polynomials) assuming the role played by complex scalars in traditional matrix algebra, we adapt standard eigenvalue routines, factorizations, decompositions, and mat ..."
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Cited by 77 (0 self)
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A general tool for multichannel and multipath problems is given in FIR matrix algebra. With Finite Impulse Response (FIR) filters (or polynomials) assuming the role played by complex scalars in traditional matrix algebra, we adapt standard eigenvalue routines, factorizations, decompositions, and matrix algorithms for use in multichannel /multipath problems. Using abstract algebra/group theoretic concepts, information theoretic principles, and the Bussgang property, methods of single channel filtering and source separation of multipath mixtures are merged into a general FIR matrix framework. Techniques developed for equalization may be applied to source separation and vice versa. Potential applications of these results lie in neural networks with feedforward memory connections, wideband array processing, and in problems with a multiinput, multioutput network having channels between each source and sensor, such as source separation. Particular applications of FIR polynomial matrix alg...
A Practical Methodology for Speech Source Localization With Microphone Arrays
, 1996
"... Electronically steerable arrays of microphones have a variety of uses in speech data acquisition systems. Applications include teleconferencing, speech recognition and speaker identification, sound capture in adverse environments, and biomedical devices for the hearing impaired. An array of micropho ..."
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Cited by 60 (3 self)
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Electronically steerable arrays of microphones have a variety of uses in speech data acquisition systems. Applications include teleconferencing, speech recognition and speaker identification, sound capture in adverse environments, and biomedical devices for the hearing impaired. An array of microphones has a number of advantages over a singlemicrophone system. It may be electronically aimed to provide a highquality signal from a desired source location while simultaneously attenuating interfering talkers and ambient noise, does not necessitate local placement of transducers or encumber the talker with a handheld or headmounted microphone, and does not require physical movement to alter its direction of reception. Additionally, it has capabilities that a single microphone does not; namely automatic detection, localization, and tracking of active talkers in its receptive area. This paper addresses the specific application of source localization algorithms for estimating the position ...
A Framework for Speech Source Localization Using Sensor Arrays
, 1995
"... Electronically steerable arrays of microphones have avariety of uses in speech data acquisition systems. Applications include teleconferencing, speech recognition and speaker identification, sound capture in adverse environments, and biomedical devices for the hearing impaired. An array of microph ..."
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Cited by 54 (5 self)
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Electronically steerable arrays of microphones have avariety of uses in speech data acquisition systems. Applications include teleconferencing, speech recognition and speaker identification, sound capture in adverse environments, and biomedical devices for the hearing impaired. An array of microphones has a number of advantages over a singlemicrophone system. It may be electronically aimed to provide a highquality signal from a desired source location while simultaneously attenuating interfering talkers and ambient noise, does not necessitate local placement of transducers or encumber the talker with a handheld or headmounted microphone, and does not require physical movement to alter its direction of reception. Additionally, it has capabilities that a single microphone does not; namely automatic detection, localization, and tracking of active talkers in its receptive area. A fundamental requirement of sensor array systems is the ability to locate and track a speech source. An accurate fix on the primary talker, as well as knowledge of any interfering talkers or coherent noise sources, is necessary to effectively steer the array. Source location data may also be used for purposes other than beamforming; e.g. aiming a camera in a videoconferencing system. In addition to high accuracy, the location estimator must be
The Fusion of Distributed Microphone Arrays for Sound Localization
"... This paper presents a general method for the integration of distributed microphone arrays for localization of a sound source. The recently proposed sound localization technique known as SRPPHAT is shown to be a special case of the more general microphone array integration mechanism presented here. ..."
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Cited by 28 (7 self)
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This paper presents a general method for the integration of distributed microphone arrays for localization of a sound source. The recently proposed sound localization technique known as SRPPHAT is shown to be a special case of the more general microphone array integration mechanism presented here. The proposed technique utilizes spatial likelihood functions (SLFs) produced by each microphone array and integrates them using a weighted addition of the individual SLFs. This integration strategy accounts for the dierent levels of access that a microphone array has to different spatial positions, resulting in an intelligent integration strategy that weighs the results of reliable microphone arrays more significantly. Experimental results using 10 2element microphone arrays show a reduction in the sound localization error from 0.9m to 0.08m at a signalto noise ratio of 0dB. The proposed technique also has the advantage of being applicable to multimodal sensor networks.
Signal reconstruction in sensor arrays using sparse representations $
, 2005
"... We propose a technique of multisensor signal reconstruction based on the assumption, that source signals are spatially sparse, as well as have sparse representation in a chosen dictionary in time domain. This leads to a large scale convex optimization problem, which involves combined l1l2 norm mini ..."
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Cited by 18 (0 self)
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We propose a technique of multisensor signal reconstruction based on the assumption, that source signals are spatially sparse, as well as have sparse representation in a chosen dictionary in time domain. This leads to a large scale convex optimization problem, which involves combined l1l2 norm minimization. The optimization is carried by the truncated Newton method, using preconditioned conjugate gradients in inner iterations. The byproduct of reconstruction is the estimation of source locations. r 2005 Published by Elsevier B.V.
Applications of a 3D microphone array
 in Preprint 112th
, 2002
"... This convention paper has been reproduced from the author’s advance manuscript, without editing, corrections, or consideration by the Review Board. The AES takes no responsibility for the contents. Additional papers may be ..."
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Cited by 7 (0 self)
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This convention paper has been reproduced from the author’s advance manuscript, without editing, corrections, or consideration by the Review Board. The AES takes no responsibility for the contents. Additional papers may be
Broadband DOA Estimation Using "SpatialOnly" Modeling of Array Data
 IEEE Transactions on Signal Processing
, 2000
"... Most of the existing techniques for DOA estimation of broadband sources use both spatial and temporal modeling. This may lead to increased complexity besides a large algorithmic delay. In this paper, we propose a technique that employs only spatial information in the form of a single spatial array c ..."
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Cited by 6 (1 self)
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Most of the existing techniques for DOA estimation of broadband sources use both spatial and temporal modeling. This may lead to increased complexity besides a large algorithmic delay. In this paper, we propose a technique that employs only spatial information in the form of a single spatial array covariance matrix. Assuming the source to have an ideal bandpass power spectral density, we formulate two subspacebased search functions for the estimation of DOA's of broadband sources. One of these employs a multidimensional search in the parameter space, whereas the other requires a MUSIC like onedimensional (1D) search. The multidimensional cost function is shown to be consistent, yields performance close to the CR bound, and is insensitive to correlation between sources. Both the proposed methods are shown to be robust to deviations from the assumption of ideal bandpass power spectral density used in their formulation. I.
DOA Estimation of Wideband Sources Using a Harmonic Source Model and Uniform Linear Array
 IEEE Trans. Signal Processing
, 1999
"... We consider here the problem of estimation of DOA's of multiple wideband sources incident on a uniform linear array (ULA) in the presence of spatially and temporally white Gaussian noise (WGN). The approach presented here builds up on the IQML algorithm suggested by Bresler and Macovski for the ..."
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Cited by 6 (0 self)
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We consider here the problem of estimation of DOA's of multiple wideband sources incident on a uniform linear array (ULA) in the presence of spatially and temporally white Gaussian noise (WGN). The approach presented here builds up on the IQML algorithm suggested by Bresler and Macovski for the case of narrowband DOA estimation. It is shown that the concept of ARMA model for the observed data vector for the narrowband case can be generalized to model an appropriately stacked, spacetime data vector obtained by combining the spacetime samples. The coefficients of the corresponding 2D predictor polynomial can be used to represent the null subspace of the wideband array steering matrix, and rooting of the polynomial at each frequency, separately, gives the DOA estimates. These separate estimates at multiple frequencies are combined into a single DOA estimate in a least squares sense. This leads to the formulation of an IQMLlike procedure for the spatial parameter estimation of wideband sources. Like its narrowband counterpart, the proposed approach is applicable to both noncoherent and coherent sources. The performance of the proposed method is studied via extensive computer simulations and by comparison with the CR bounds. Index Terms Array signal processing, broadband sources, directionofarrival estimation, maximum likelihood techniques, special ARMA model, uniform linear array. I.
Coherent Broadband Source Localization by Modal Space
"... A novel method for coherent broadband direction of arrival (DOA) estimation is introduced based on physics of signal propagation. This technique does not require any preliminary knowledge of DOA angles nor the number of sources to be estimated. As an illustration, two simulation examples covering si ..."
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Cited by 5 (2 self)
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A novel method for coherent broadband direction of arrival (DOA) estimation is introduced based on physics of signal propagation. This technique does not require any preliminary knowledge of DOA angles nor the number of sources to be estimated. As an illustration, two simulation examples covering single and multigroup scenarios are presented.