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Consensus for distributed EM-based clustering in WSNs

Consensus for distributed EM-based clustering in WSNs

引用

sensor array and multichannel signal processing workshop

作者： Silvana Silva Pereira Sergio Barbarossa Alba Pagès-Zamora SPCOM Group Universitat Politècnica de Catalunya-Barcelona Tech (UPC) Barcelona Spain INFOCOM Dpt. Sapienza University of Rome Rome Italy

A distributed EM algorithm with consensus is proposed for density estimation and clustering using WSNs in the presence of mixtures of Gaussians. The EM algorithm is a general framework for maximum likelihood estimation in hidden variable models, usually implemented in a central node with global information of the network. The average consensus algorithm is a simple robust scheme for computing averages in a distributed manner. In this contribution, we run a distributed EM algorithm where the nodes obtain global knowledge of the statistics through consensus with local information exchange only in a WSN with instantaneous random links. Starting from a set of initial values, the nodes are able to compute the complete statistics of a mixture of Gaussians and classify into clusters according to the sensed density using a simple decision rule. A trade off between power consumption and final accuracy of the estimates is established through simulations.

关键词： Clustering algorithms Wireless sensor networks Estimation Convergence signal processing algorithms Classification algorithms Topology

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Vectored VDSL from a practical perspective: ISmart FEXT cancellation performance

Vectored VDSL from a practical perspective: ISmart FEXT canc...

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sensor array and multichannel signal processing workshop

作者： Ronen Yizhaq Gilad Elad Domanovitz Amit Priebatch Ilan Sharfer Avi Matza Eitan Tsur Product Innovation Actelis Networks Limited Petach Tikva Israel Access Research and Development Network Solutions Division ECI Telecom Limited Petach Tikva Israel

Far End Crosstalk (FEXT) in a twisted pair cable is the most dominant noise impairment in short loops for VDSL2 systems. Its impact significantly reduces the VDSL2 modems performance and in some cases might reduce the modem throughput by more than 50%. Canceling the FEXT impact using Dynamic Spectral Management Level 3 (DSM L3, aka Vectoring aka FEXT Cancellation) is an emerging technology for high rates data traffic over copper (Up to 100Mbit/sec). We have developed an eight VDSL2 modems prototype with DSM L3 capabilities. In this article we introduce an overview of our system design and a variety of tests results that reflect the DSM L3 potential.

关键词： Modems Crosstalk DSL Estimation Conferences signal processing Copper

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Order-preserving factor discovery from misaligned data

Order-preserving factor discovery from misaligned data

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sensor array and multichannel signal processing workshop

作者： Arnau Tibau Puig Ami Wiesel Aimee Zaas Geoffrey S. Ginsburg Gilles Fleury Alfred O. Hero Department of Electrical Engineering University of Michigan USA Electronic Systems Department SUPELEC Systems Sciences Signal Processing France Division of Infectious Diseases and International Health Department of Medicine School of Medicine Duke University USA Institute of Genome Sciences & Policy Duke University USA

We present a factor analysis method that accounts for possible temporal misalignment of the factor loadings across the population of samples. Our main hypothesis is that the data contains a subset of variables with similar but delayed profiles obeying a consistent precedence ordering relationship. Our model is motivated by the difficulty of gene expression analysis across subjects who have common patterns of immune response but show different onset times after a uniform innoculation time of a viral pathogen. The proposed method is based on a linear model with additional degrees of freedom that account for each subject's inherent delays. We present an algorithm to fit this model in a totally unsupervised manner and demonstrate its effectiveness on extracting gene expression factors affecting host response using a flu-virus human challenge study dataset.

关键词： Gene expression Sparse matrices signal processing algorithms Principal component analysis Dictionaries Data models Approximation algorithms

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Joint channel estimation and Markov Chain Monte Carlo detection for frequency-selective channels

Joint channel estimation and Markov Chain Monte Carlo detect...

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sensor array and multichannel signal processing workshop

作者： Hong Wan Rong-Rong Chen Jun Won Choi Andrew Singer James Preisig Behrouz Farhang-Boroujeny Département de Physique Théorique et appliquée Commissariat Energie Atomique Bruyeres-le-Cheitel France Dept. of Microelectronics Soochow University Suzhou China STMicroelectronics Crolles France Dept. of Electronic and Computer Engineering The Hong Kong University of Science and Technology Kowloon Hong Kong China

In this paper, we develop a novel approach for joint channel estimation and Markov Chain Monte Carlo (MCMC) detection for time-varying frequency-selective channels. First, we propose a sequential channel estimation (SCE) MCMC algorithm that combines an MCMC algorithm for data detection, and an adaptive least mean square (LMS) algorithm for channel tracking, in a sequential fashion. Then we develop a stochastic expectation maximization (SEM) MCMC algorithm that takes advantage of both the MCMC approach and the EM algorithm to find jointly important samples of the transmitted data and channel impulse response (CIR). The proposed algorithms provide a low-complexity means to approximate the optimal maximum a posterior (MAP) detection in a statistical fashion and are applicable to channels with long memory. Excellent behavior of the proposed algorithms is presented using both synthetic channels and real data collected from actual underwater acoustic experiments.

关键词： Channel estimation Detectors Least squares approximation Decoding Markov processes Joints signal processing algorithms

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Multi-channel reconstruction from a randomly sampled array

Multi-channel reconstruction from a randomly sampled array

引用

ieee International workshop on Computational Advances in Multi-sensor Adaptive processing (CAMSAP)

作者： Ryan B. Casey Kenneth M. Pesyna Christopher B. Smith Southwest Research Institute San Antonio TX USA Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA

ISBN: (纸本)9781424451791;9781424451807

Compressive sampling has a rich theoretical background in a number of fields from image processing to medical imaging to geophysical data analysis. In this paper we explore compressive sampling from the perspective of classic array processing. We derive a basis appropriate for reconstructing multichannel data which is sparsely sampled from a uniform linear array. Here we reconstruct both time and spatial components of the signal using randomly sampled time series. We present both theoretical and experimental evidence that compressive sampling can be successful for traditional array processing applications.

关键词： Image coding Image reconstruction Image sampling signal sampling array signal processing Image processing Costs Linear antenna arrays Hardware Partial differential equations

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BSS for improved interference estimation for Blind speech signal Extraction with two microphones

BSS for improved interference estimation for Blind speech si...

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ieee International workshop on Computational Advances in Multi-sensor Adaptive processing (CAMSAP)

作者： Yuanhang Zheng Klaus Reindl Walter Kellermann Multimedia Communications and Signal Processing University of Erlangen Nuremberg Erlangen Germany

ISBN: (纸本)9781424451791;9781424451807

Blind source extraction (BSE) as desirable for acoustic cocktail party scenarios requires estimates for the target or interfering signals. Conventional single-channel approaches for obtaining the interference estimate rely on noise and interference estimates during absence of the target signal. For multichannel approaches using multiple microphone signals, a separation of simultaneously active target and interference signals becomes possible if the positions of the target and interfering sources are known. We propose a new method which exploits directional BSS (blind source separation with a geometric constraint) to estimate the interfering speech sources and diffuse background noise jointly and blindly. Herewith we can effectively deal with the underdetermined BSS scenario (more point sources than sensors) in reverberant environments and can even allow for additional babble noise in the background.

关键词： Interference Microphones Source separation Speech enhancement Background noise sensor arrays MIMO signal processing Blind source separation array signal processing

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LOCALIZATION OF DIFFRACTED SEISMIC NOISE SOURCES USING AN array OF SEISMIC sensorS

LOCALIZATION OF DIFFRACTED SEISMIC NOISE SOURCES USING AN AR...

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ieee sensor array and multichannel signal processing workshop

作者： Gulunay, Necati CGGVeritas R&D Cairo Egypt

Seismic receiver arrays that are used in modem 3D marine surveys can also be used as 2D sensor arrays in the localization of the diffracted noise sources and hence allow attenuation of such noise from the seismic reco... 详细信息

ISBN: (纸本)9781424422401

关键词： Seismology

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PERFORMANCE ANALYSIS OF ROOT-MUSIC-BASED DIRECTION-OF-ARRIVAL ESTIMATION FOR ARBITRARY NON-UNIFORM arrayS

PERFORMANCE ANALYSIS OF ROOT-MUSIC-BASED DIRECTION-OF-ARRIVA...

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ieee sensor array and multichannel signal processing workshop

作者： Ruebsamen, Michael Gershman, Alex B. Tech Univ Darmstadt Commun Syst Grp D-64283 Darmstadt Germany

We present the asymptotic performance analysis of the interpolated root-MUSIC and manifold separation (MS) techniques for direction-of-arrival (DOA) estimation in arbitrary non-uniform sensor arrays. Our analysis take... 详细信息

ISBN: (纸本)9781424422401

关键词： Direction-of-arrival estimation non-uniform sensor arrays root-MUSIC sensor array processing

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BEAMSPACE ADAPTIVE BEAMFORMING BASED ON PRINCIPLE COMPONENT ANALYSIS

BEAMSPACE ADAPTIVE BEAMFORMING BASED ON PRINCIPLE COMPONENT ...

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ieee sensor array and multichannel signal processing workshop

作者： Yu, Lei Liu, Wei Langley, Richard Univ Sheffield Dept Elect & Elect Engn Commun Res Grp Sheffield S10 2TN S Yorkshire England

ISBN: (纸本)9781424422401

A novel adaptive beamforming method is proposed without the knowledge of the direction of arrival of the signal of interest. It is a combination of the traditional beamspace processing method and a recently proposed technique called "Domain Weighted Principal Component Analysis (DW-PCA)" and can be applied to the case where the signal of interest is stronger than the interfering signals in both single-path and multi-path environments. Its effectiveness is verified by simulation results.

关键词： adaptive systems array signal processing multipath channels

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POWER-AWARE DISTRIBUTED DETECTION IN IR-UWB sensor NETWORKS

POWER-AWARE DISTRIBUTED DETECTION IN IR-UWB SENSOR NETWORKS

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ieee sensor array and multichannel signal processing workshop

作者： Bielefeld, Daniel Fabeck, Gernot Mathar, Rudolf Univ Aachen Rhein Westfal TH Aachen Inst Theoret Informat Technol D-5100 Aachen Germany

ISBN: (纸本)9781424422401

The interplay between signal processing and wireless networking plays a crucial role in sensor networks deployed for detection and estimation applications. In this paper, an opportunistic power assignment strategy for IR-UWB sensor networks is presented which is designed to optimize detection performance in terms of the global probability of error. The opportunistic power assignment strategy utilizes both the detection error probabilities of individual sensors as well as network topology information, leading to significant performance gains compared to uniform power assignment.

关键词： Ultra-wideband (UWB)

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