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A CLOSED-FORM SOLUTION FOR MULTILINEAR PARAFAC DECOMPOSITIONS

A CLOSED-FORM SOLUTION FOR MULTILINEAR PARAFAC DECOMPOSITION...

引用

ieee sensor array and multichannel signal processing workshop

作者： Roemer, Florian Haardt, Martin Tech Univ Ilmenau Commun Res Lab D-98684 Ilmenau Germany

ISBN: (纸本)9781424422401

In this paper we study the R-way Parallel Factor Analysis (also referred to as R-way PARAFAC) problem. This branch of multi-way signal processing has received increased attention recently which is due to the versatility of the model as well as the identifiability results demonstrating its superiority to matrix-only (2-way) approaches. In R-way PARAFAC analysis, the goal is to decompose an R-dimensional tensor into a minimal sum of rank-1 terms. So far, there exist sub-optimal closed-form solutions as well as iterative techniques for finding these decompositions. However, the latter often require many iterations to converge. In this contribution we demonstrate that the R-way PARAFAC decomposition can be reduced to a set of simultaneous matrix diagonalization problems. Exploiting the structure of the R-dimensional problem, we obtain several estimates for each of the factors and present a "best matching" scheme to select the best estimate for each factor. By means of computer simulations we compare our closed-form solution to an iterative technique and demonstrate the enhanced robustness in critical scenarios.

关键词： Multidimensional signal processing Parameter estimation array signal processing

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Mitigating Outliers for Bayesian Mixture of Factor Analyzers 11

Mitigating Outliers for Bayesian Mixture of Factor Analyzers

引用

ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Chen, Zhongtao Cheng, Lei Shenzhen Res Inst Big Data Shenzhen Peoples R China Chinese Univ Hong Kong Shenzhen Peoples R China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119465

The Bayesian mixture of factor analyzers (BMFA), which achieves joint clustering and dimensionality reduction, is with an appealing feature of automatic hyper-parameter learning. In addition to its great success in various unsupervised learning tasks, it exemplifies how the Bayesian statistics can be leveraged to achieve automatic hyper-parameter learning, which is an open problem of modern simultaneous (deep) dimensionality reduction and clustering. Due to the importance of the BMFA, in this paper, its mechanism is carefully investigated, and a robust variant of the BMFA that can mitigate potential outliers is further proposed. Numerical studies are presented to show the remarkable performance of the proposed algorithm in terms of accuracy and robustness.

关键词： Dimensionality reduction array signal processing Conferences signal processing algorithms Clustering algorithms Robustness Bayes methods

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Early experimental results for a large-aperture microphone-array system

Early experimental results for a large-aperture microphone-a...

引用

1st ieee sensor array and multichannel signal processing workshop (SAM 2000)

作者： Silverman, HF Patterson, WR Sachar, JM Brown Univ Div Engn LEMS Providence RI 02912 USA

ISBN: (纸本)0780363396

Microphone arrays offer a potential solution to the important problem of obtaining high-quality sound pick-up from remote acoustic sources. Most reported results for microphone array technology have been theoretical, proposed algorithms with predicted performance, or based on ideal or near-ideal simulations of microphonearray systems and room environments. Previous work that is based on real data has usually been for a small number of microphones. In this paper, for the first time, measured results for a large number of microphones, 256, in a large-aperture, real-time, all DSP system are reported. The array system is mounted in a moderate-sized (8Mx8M) room with a significant reverberation time. While listeners to the locationing/tracking/beamforming system claim to hear near-close-talking microphone performance when the system acquires a talker, our measured results of the real-time system indicate that a true 9dB separation of a source from other sources in the room has been achieved and that reverberant effects have been significantly reduced. This level of isolation is maintained at all locations throughout the room. In addition to reporting these early performance measures, this paper discusses the nuances of the real-time algorithms, the latency in such systems, and introduces some of the issues of making real-time, real-room measurements.

关键词： Acoustic arrays array signal processing Delay Digital signal processing Microphone arrays Prediction algorithms Predictive models Real time systems Reverberation Time measurement

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Blind source separation for solid-state chemical sensor arrays

Blind source separation for solid-state chemical sensor arra...

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3rd ieee sensor array and multichannel signal processing workshop

作者： Bermejo, S Solé-Casals, J Univ Politecn Catalunya Dept Elect Engn ES-08034 Barcelona Spain

ISBN: (纸本)0780385454

Electronic noses and tongues are two recent examples in chemical sensing that employ statistical array techniques in order to overcome the intrinsic limitations of current solid-state chemical sensors like ion-selective field transistors (ISFET). In particular, ISFETs are sensitive to the concentration of a particular ion in a solution to be measured, but it can be also strongly affected by several interfering ions found in the solution. Hence, they must be employed in regions in which the effect of interferences is negligible thus limiting their range of operation. However, since ISFETs behave as non-linear mixers of main ion activities and interfering ones, an attempt to separate the original main ion activity and interferences from the mixed response is suitable with blind source separation (BSS) techniques and related methods like independent component analysis (ICA) methods. In this direction, several experiments with real ISFET measurements demonstrate the interest of employing BSS for dealing with the separation in ISFET responses, and further reconstruction, of ion activities in those operating regions in which interferences notably affect their response.

关键词： Blind source separation

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Joint Range, Angle and Doppler Estimation for FDA-MIMO Radar 10

Joint Range, Angle and Doppler Estimation for FDA-MIMO Radar

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10th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Xu, Jian Wang, Wen-Qin Cui, Can Gui, Ronghua Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 611731 Sichuan Peoples R China

ISBN: (纸本)9781538647523

Frequency diverse array (FDA) radar for joint range and angle estimation has drawn much attention, but Doppler estimation is often ignored in the literature. In this paper, we propose joint range, angle and Doppler estimation for FDA-multiple-input multiple-output (FDA-MIMO) radar. In order to reduce the computation complexity, the Doppler is independently estimated firstly by the extended invariance principle instead of maximum likelihood (ML) estimator. Next, the range and angle are estimated separately with the unstructured model. That is, the three-dimensional search problem of joint range, angle and Doppler estimation is simplified into three one-dimensional search problems. The superiorities of the proposed method over conventional ML algorithms are verified by numerical results.

关键词： Doppler effect Doppler radar array signal processing Maximum likelihood estimation sensor arrays"

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sensor array shape estimation using active sonar clutter

Sensor array shape estimation using active sonar clutter

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2nd ieee sensor array and multichannel signal processing workshop

作者： Varadarajan, V Krolik, J Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

ISBN: (纸本)0780375513

This paper concerns the problem of array shape estimation from clutter (ASEC) for a towed active sonar array. Although heading sensors can provide towed-array shape information, they are sometimes not sufficiently available or accurate to facilitate beamforming with low sidelobe levels necessary for detection of low-Doppler targets, especially in the presence of severe bottom reverberation. We propose a maximum likelihood array shape calibration technique that exploits the azimuth-Doppler frequency relationship of the clutter by fitting the reverberation snapshots from a single sonar ping to the low rank space-time clutter subspace.

关键词： Sonar

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Sparse signal Recovery Using a Binary Program 12

Sparse Signal Recovery Using a Binary Program

引用

ieee 12th sensor array and multichannel signal processing workshop (SAM)

作者： Rahman, Muhammed Tahsin Valaee, Shahrokh Univ Toronto Elect & Comp Engn Toronto ON Canada

ISBN: (纸本)9781665406338

Sparsity based signal recovery has seen great success in solving underdetermined systems of equations. This success is due, in large part, to a relaxation: the l0-norm is replaced by the l1-norm, which results in a convex problem. However, such a relaxation may lead to a suboptimal solution, one that may even be asymptotically biased. We propose formulating sparse signal recovery as a binary program, and we derive the conditions under which such a formulation perfectly recovers the signal support. This derivation equips us with a constraint on the dictionary's spectrum. However, designing such a dictionary is a combinatorial problem, so we suggest a heuristic which can be readily satisfied using the alternating projections algorithm. Applied to angle of arrival (AoA) estimation using a sensor array, we show how this paradigm outperforms both the basis pursuit l1-norm relaxation and the Matrix Pencil method.

关键词： Binary program sparsity compressed sensing angle of arrival estimation antenna array

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processing-aware compression for sensor networks

Processing-aware compression for sensor networks

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2nd ieee sensor array and multichannel signal processing workshop

作者： Vasudevan, L Ortega, A Univ So Calif Dept Elect Engn Inst Signal & Image Proc Integrated Media Syst Ctr Los Angeles CA 90089 USA

ISBN: (纸本)0780375513

In sensor networks, where power and bandwidth are at a premium, there is a clear need to use compression to limit the amount of information exchanged by the sensors. In this paper we study the signal compression problem in situations where signals are being processed for the purpose of source localization. In these scenarios compression should be optimized for the accuracy of source localization, rather than to provide a reproduction of the signals with some desired fidelity. We show how this leads to novel design techniques that have clear advantages over standard quantizer design approaches.

关键词： sensor networks

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A new beamformer based on phase dispersion to improve 2D sparse array response

A new beamformer based on phase dispersion to improve 2D spa...

引用

ieee 7th sensor array and multichannel signal processing workshop (SAM)

作者： Martinez-Graullera, Oscar Romero-Laorden, David Ibanez, Alberto Ullate, Luis G. CAEND UPM CSIC Madrid 28006 Spain

ISBN: (纸本)9781467310710

This work studies a new beamformer for non-periodic sparse bidimensional ultrasonic array transducer. It is based on a weighting factor based on signals phase dispersion to enhance the image points where the phase coherence between the received signals is high. A method to measure the phase dispersion based on Fourier analysis and its integration in the beamformer are presented. Its performance is evaluated using a non-periodic 2D sparse array based on Fermat spiral with 96 elements and a diameter of 60 lambda. Compared with conventional Delay-And-Sum beamformer the proposed solution reduces the aperture lateral resolution and improves its dynamic range, achieving up to 50dB of contrast in the image and less 1 degrees in lateral resolution.

关键词： Fourier analysis

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Data orthogonalization in sensor array signal processing

Data orthogonalization in sensor array signal processing

引用

2nd ieee sensor array and multichannel signal processing workshop

作者： Owsley, NL Off Naval Res Arlington VA 22217 USA

ISBN: (纸本)0780375513

In this primarily tutorial paper, a perspective on the development of Adaptive Data Orthogonalization (ADO) for spatial sensor array sampled data vectors is presented. The development of ADO methods is traced from a generalization of the split array, cross-correlation arrival angle tracker for a single source, plane wave arrival to multiple coherent arrivals. Development is followed through to the more recent maximization of the ratio of two quadratic forms that expresses beamformer array gain. Specifically, the reduced complexity implementation of a signal model error robust Minimum Variance Distortionless Response (MVDR) Adaptive Beamformer (ABF) is described. This robust beamformer is a simple, explicit linear blend (combination) of the inherently robust shaded time delay-and-sum Conventional Beamformer (CBF) and the Enhanced Minimum Variance (EMV) Dominant Mode Rejection (DMR) ABF. This ABF construction places an easily implemented upper bound on the signal suppression caused by signal model mismatch and allows a trade-off between spatial resolution and Main Lobe signal Maintenance (MLM). Several methods for robust DMR ABF are compared.

关键词： array processing

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