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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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Blind source separation for solid-state chemical sensor arrays

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

引用

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

引用

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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multichannel signal processing methods for ultrasonic nondestructive evaluation

Multichannel signal processing methods for ultrasonic nondes...

引用

2nd ieee sensor array and multichannel signal processing workshop

作者： Ramuhalli, P Kim, J Udpa, L Udpa, SS Michigan State Univ Dept Elect & Comp Engn E Lansing MI 48824 USA

ISBN: (纸本)0780375513

Ultrasonic inspection methods are commonly used in the nondestructive evaluation of welds to detect flaws in the weld region. An important characteristic of ultrasonic inspection is the ability to identify the type of discontinuity that gives rise to a particular signal. Standard techniques rely on differences in individual A-scans to classify the signals. This paper proposes an ultrasonic signal classification technique based on the information in a group of signals. The approach is based on a 2-dimensional transform and principal component analysis, for generating a reduced dimensional feature vector for classification. Results of applying the technique to data obtained from the inspection of welds are presented.

关键词： Welds

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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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Optimal Virtual array Length Under Position Imperfections

Optimal Virtual Array Length Under Position Imperfections

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8th ieee sensor array and multichannel signal processing workshop (SAM)

作者： Mannesson, Anders Bernhardsson, Bo Yaqoob, Muhammad Atif Tufvesson, Fredrik Lund Univ Dept Automat Control S-22100 Lund Sweden Lund Univ Dept Elect & Informat Technol S-22100 Lund Sweden

ISBN: (纸本)9781479914814

This article contains a study of how spatial errors and receiver imperfections affect the angle of arrival estimation accuracy for virtual antenna arrays. A virtual antenna array consists of one receiver element whose location is tracked as the element is moved and in this work, linear arrays are studied. If the location of the receiver is tracked using an inertial measurement unit, an interesting trade-off emerges. The array should extend as far as possible but since the position estimates from the unaided inertial measurement unit become increasingly uncertain over time, the angle of arrival estimation will deteriorate. Several algorithms are available for estimating the angle of arrival in such a scenario but the one used for evaluation here is a sparse enforcing least squares method.

关键词： Angle of arrival Antenna arrays Measurement units Receivers INERTIAL MEASUREMENT UNITS Virtual Elements

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Iterative Sparse Through-the-Wall Imaging

Iterative Sparse Through-the-Wall Imaging

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

作者： Nikolic, Marija Nehorai, Arye Djordjevic, Antonije Univ Belgrade Sch Elect Engn Bulevar Kralja Aleksandra 73 Belgrade 11000 Serbia Washington Univ Dept Elect & Syst Engn St Louis MO 63130 USA

ISBN: (纸本)9781467310710

We consider iterative electromagnetic imaging of metallic targets hidden behind dielectric walls using sparse regularization. As in the equivalent-source method, we assume that the targets can be approximated by a set of filament currents whose locations are unknown. By using the iterative procedure, we reveal additional filament currents thus enlarging the target image. In order to take into account the mutual interaction between the current sources, and yet obtain the model amenable to signal processing, we combine the method of moments and the ray tracing.

关键词： target image Ray tracing Current sources Iterative Iterative Process METHOD OF MOMENTS Cytoskeletal Filaments signal processing Imaging

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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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DOA Estimation of Quasi-Stationary signals With a Nested array in Unknown Noise Field 10

DOA Estimation of Quasi-Stationary Signals With a Nested Arr...

引用

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

作者： Huang, Huiping Liao, Bin Shen, Qiuxiang Shenzhen Univ Coll Informat Engn Shenzhen 518060 Guangdong Peoples R China

ISBN: (纸本)9781538647523

The problem of direction-of-arrival (DOA) estimation of quasi-stationary signals using a nested array in unknown noise field is investigated and two methods based on differencing method and eigenspace are proposed in this paper. Through performing differencing between the virtual received data, the unknown noise component is directly removed from the data model. The resulting data model is then utilized to find out the DOAs of the signals based on the theory of subspace. Thanks to the configuration of the nested array, it can produce large degrees of freedom (DOF) in the virtual sensor array which provides the virtual received data. These increased DOF can contribute enhanced resolution in DOA estimation. Numerical simulations of DOA estimation exhibit the effectiveness and superiority of the proposed methods.

关键词： DOA estimation quasi-stationary signals nested array unknown noise field differencing method

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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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