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On Perceptual Audio Equalization for Multiple Users in Presence of Ambient Noise 10

On Perceptual Audio Equalization for Multiple Users in Prese...

引用

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

作者： Estreder, Juan Pinero, Gema Aguirre, Fabian de Diego, Maria Gonzalez, Alberto Univ Politecn Valencia Inst Telecom & Multimedia Applicat iTEAM Valencia Spain

ISBN: (纸本)9781538647523

There are many situations where ambient noise can disturb the listening of music through loudspeakers, the most usual inside cars, trains or airplanes. A common solution is to listen to the music through headphones, but in some cases, as for the car driver, it is not allowed. Even for the rest of the passengers of a car, it would be more comfortable to listen to the music without the need of headphones. In this paper, we have implemented a single-user perceptual equalizer that presents a good behaviour similar to previous solutions, but it is based on a linear additive auditory masking model. Moreover, we propose a new strategy to obtain the gains of the perceptual equalizer that does not depend on external parameters. Our alternative approach (linear additive masking model and robust equalizer design) makes possible to extend the perceptual equalizer to the multi-user case, i.e., when more than one user are considered and their own perceptual curves are interacting in the same enclosure. Objective measurements and informal listening tests have confirmed the good behaviour of the single-user strategy.

关键词： Perceptual audio equalization ambient noise multi-user audio acoustic networks smart audio processing

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Enforcing Eigenvector Smoothness for a Compact DFT-based Polynomial Eigenvalue Decomposition 10

Enforcing Eigenvector Smoothness for a Compact DFT-based Pol...

引用

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

作者： Coutts, Fraser K. Thompson, Keith Pestana, Jennifer Proudler, Ian K. Weiss, Stephan Univ Strathclyde Dept Elect & Elect Engn Glasgow Lanark Scotland Univ Strathclyde Dept Math & Stat Glasgow Lanark Scotland

ISBN: (纸本)9781538647523

A variety of algorithms have been developed to compute an approximate polynomial matrix eigenvalue decomposition (PEVD). As an extension of the ordinary EVD to polynomial matrices, the PEVD will generate paraunitary matrices that diagonalise a parahermitian matrix. While iterative PEVD algorithms that compute a decomposition in the time domain have received a great deal of focus and algorithmic improvements in recent years, there has been less research in the field of frequency-based PEVD algorithms. Such algorithms have shown promise for the decomposition of problems of finite order, but the state-of-the-art requires a priori knowledge of the length of the polynomial matrices required in the decomposition. This paper presents a novel frequency-based PEVD algorithm which can compute an accurate decomposition without requiring this information. Also presented is a new metric for measuring a function's smoothness on the unit circle, which is utilised within the algorithm to maximise eigenvector smoothness for a compact decomposition, such that the polynomial eigenvectors have low order. We demonstrate through the use of simulations that the algorithm can achieve superior levels of decomposition accuracy to a state-of-the-art frequency-based method.

关键词： Matrix decomposition Eigenvalues and eigenfunctions signal processing algorithms Covariance matrices Approximation algorithms Measurement Linear programming"

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Short Data Record Filtering for Adaptive Underwater Acoustic Communications 10

Short Data Record Filtering for Adaptive Underwater Acoustic...

引用

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

作者： Gannon, Adam Balakrishnan, Sarankumar Sklivanitis, George Pados, Dimitris A. Batalama, Stella N. SUNY Buffalo Dept Elect Engn Buffalo NY 14260 USA Florida Atlantic Univ I SENSE Boca Raton FL 33431 USA Florida Atlantic Univ Dept Comp & Elect Engn & Comp Sci Boca Raton FL 33431 USA Florida Atlantic Univ Coll Engn & Comp Sci Boca Raton FL 33431 USA

ISBN: (纸本)9781538647523

Spread-spectrum signaling offers robust communication over the multipath underwater acoustic channel, while at the same time allows multiple users to simultaneously occupy the entire continuum of the device-accessible bandwidth. However, limitations in temporal and spatial coherence of the underwater acoustic channel affect the maximum spreading code length and therefore the effective link data rate. In this work, we propose adaptive code length optimization toward high-rate spread-spectrum underwater acoustic communications. We first evaluate the bit error rate (BER) performance of the estimated minimum variance distortionless response (MVDR) and auxiliary-vector (AV) linear filter receivers. We observe that the AV-filter based receiver significantly outperforms the estimated MVDR solution under limited data-record availability. We then investigate data rate trade-offs for optimized code lengths under pre-defined BER constraints in time-varying underwater acoustic channels. Simulation results verify that the proposed adaptive packetization scheme offers superior data rate performance under short data-record constraints imposed by the non-stationary nature of the underwater environment.

关键词： Receivers Underwater acoustics Interference signal to noise ratio Coherence Bit error rate array signal processing"

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Optimal signalling for Massive SIMO Channels 10

Optimal Signalling for Massive SIMO Channels

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

作者： Gao, Xiang-Chuan Zhang, Jian-Kang Jin, Jin Zhengzhou Univ Sch Informat & Engn Zhengzhou Henan Peoples R China McMaster Univ Dept Elect & Comp Engn Hamilton ON Canada

ISBN: (纸本)9781538647523

This paper focuses on a noncoherent flat Rayleigh fading wireless communication system with a single transmitter antenna and N receiver antennas, i.e., a single-input-multiple-output (SIMO) system, in which the channel coefficients vary in every one time slot. For such a system, a fast noncoherent maximum likelihood (ML) detection algorithm and a corresponding closed form symbol error probability (SEP) formula are derived. In addition, the lower and upper bounds on SEP are established to quantitatively characterize how quickly SEP decays when N goes to infinity, with two important concepts, full receiver diversity gain and geometrical coding gain, being introduced, showing that any nonnegative pulse amplitude modulation (PAM) constellation enables full receiver diversity for the massive SIMO system. Furthermore, we find that an optimal received constellation that maximizes the geometrical coding gain is the geometrical constellation. Comprehensive computer simulations validate our theoretical analysis and demonstrate that our proposed optimal constellation attains significant performance gains over the currently available constellation design for the same massive SIMO system.

关键词： Receiving antennas Transmitting antennas Detectors MIMO communication signal processing"

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ROBUST SPARSE PHASE RETRIEVAL FROM DIFFERENTIAL MEASUREMENTS USING REWEIGHTED L₁ MINIMIZATION 10

ROBUST SPARSE PHASE RETRIEVAL FROM DIFFERENTIAL MEASUREMENTS...

引用

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

作者： Sarangi, Pulak Pal, Piya Univ Calif San Diego Dept Elect & Comp Engn San Diego CA 92103 USA

ISBN: (纸本)9781538647523

We consider the problem of sparse Fourier phase retrieval where the goal is to recover a sparse signal from the magnitudes of its Fourier transform. In our earlier work, it was shown that using a certain differential measurement model, it is possible to perform sparse Fourier phase retrieval with near-minimal sample complexity. Such measurements are realizable using interferometric imaging techniques and can remove the ambiguities inherent in Fourier phase retrieval in the noiseless setting. However, in presence of noise, such a differential measurement model can potentially lead to noise amplification and degrade the performance as sparsity increases. To address this issue, we propose to use a reweighted l(1) minimization algorithm in conjunction with our differential measurement model. Reweighted l(1) minimization has been successfully adopted in compressed sensing where it shows good performance in presence of large sparsity. We demonstrate a sparse phase retrieval algorithm based on reweighted l(1) minimization which shows superior performance in low signal to Noise ratio (SNR) and high sparsity regime.(1)

关键词： Minimization signal processing algorithms Phase measurement signal to noise ratio Extraterrestrial measurements Robustness Noise measurement"

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Consistent Least Squares Estimator for Co-array-Based DOA Estimation 10

Consistent Least Squares Estimator for Co-Array-Based DOA Es...

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10th ieee sensor array and multichannel signal processing workshop, SAM 2018

作者： Sedighi, Saeid Bhavani, Shankar Mysore R. Maleki, Sina Ottersten, Bjorn University of Luxembourg Luxembourg

ISBN: (纸本)9781538647523

Sparse linear arrays (SLAs), such as nested and co-prime arrays, have the attractive capability of providing enhanced degrees of freedom by exploiting the co-array model. Accordingly, co-array-based Direction of Arrivals (Doas) estimation has recently gained considerable interest in array processing. The literature has suggested applying MUSIC on an augmented sample covariance matrix for co-array-based Doas estimation. In this paper, we propose a Least Squares (LS) estimator for co-array-based DoAs estimation employing the covariance fitting method as an alternative to MUSIC. We show that the proposed LS estimator provides consistent estimates of Doas of identifiable sources for SLAs. Additionally, an analytical expression for the large sample performance of the proposed estimator is derived. Numerical results illustrate the finite sample behavior in relation to the derived analytical expression. Moreover, the performance of the proposed LS estimator is compared to the co-array-based MUSIC. © 2018 ieee.

关键词： Direction of arrival

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Track Management in Multiple-Hypothesis Tracking

Track Management in Multiple-Hypothesis Tracking

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sensor array and multichannel signal processing workshop

作者： Stefano Coraluppi Craig Carthel Systems & Technology Research Suite Woburn MA USA

This paper proposes an improved scheme for track management in track-oriented multiple-hypothesis tracking. We demonstrate improved performance on simulated 2D target scenarios with linear measurements.

关键词： Target tracking Trajectory Data mining array signal processing sensor arrays Conferences

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Sparse Bayesian Learning for DOA Estimation of Correlated Sources

Sparse Bayesian Learning for DOA Estimation of Correlated So...

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sensor array and multichannel signal processing workshop

作者： Christoph F. Mecklenbriiuker Peter Gerstoft Geert Leus Inst. of Telecommunications Wien Austria University of California San Diego Dept. of Electrical Eng. Delft Univ. of Technology

Direction of arrival (DOA) estimation from array observations in a noisy environment is discussed. The source amplitudes are assumed to be correlated zero-mean complex Gaussian distributed with unknown covariance matrix. The DOAs and covariance parameters of plane waves are estimated from multi-snapshot sensor array data using sparse Bayesian learning (SBL). The performance of SBL is evaluated in terms of the fidelity of the reconstructed coherency matrix of the estimated plane waves.

关键词： Covariance matrices Direction-of-arrival estimation sensor arrays Estimation array signal processing signal processing algorithms

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Symmetric Sparse Linear array for Active Imaging

Symmetric Sparse Linear Array for Active Imaging

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sensor array and multichannel signal processing workshop

作者： Robin Rajamäki Visa Koivunen Department of Signal Processing and Acoustics Aalto University Espoo Finland

Sparse sensor arrays can achieve significantly more degrees of freedom than the number of elements by leveraging the co-array, a virtual structure that arises from the far field narrowband signal model. Although several sparse array configurations have been developed for passive sensing tasks, less attention has been paid to arrays suitable for active sensing. This paper presents a novel active sparse linear array, called the Interleaved Wichmann array (IWA). The IWA only has a few closely spaced elements, which may make it more robust to mutual coupling effects. Closed-form expressions are provided for the key properties of the IWA. The parameters maximizing the array aperture for a given even number of elements are also found. The near field wideband performance of the array is demonstrated numerically in a coherent imaging scenario.

关键词： sensor arrays array signal processing Apertures Imaging Delays Wideband

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Transmitted Beampattern Synthesis with Waveform Diverse arrays Based on Arctangent Function

Transmitted Beampattern Synthesis with Waveform Diverse Arra...

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sensor array and multichannel signal processing workshop

作者： Zhonzhan Wang Yaoliang Song Tong Mu School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China

In this paper, we apply a nonlinear frequency modulation scheme based on arctangent function to waveform diverse array system to design a transmitted beampattern to focus the signal power at a specific position. Distinct from most of the existing methodologies, the proposed method overcomes the problem that the focusing performance of the signal power will decrease when considering the propagation process of the transmitted signal. As a result, the transmitted signal power can be focused at a desired position and be lasting for a period of time. Numerical simulations validate the theoretical analysis of the proposed methodology.

关键词： array signal processing sensor arrays Conferences IP networks

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