2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)最新文献_第10页

Sparsity-aware direction finding for strictly non-circular sources based on rank minimization 基于秩最小化的严格非圆源稀疏感知测向

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569715

Jens Steinwandt, Christian Steffens, M. Pesavento, M. Haardt

{"title":"Sparsity-aware direction finding for strictly non-circular sources based on rank minimization","authors":"Jens Steinwandt, Christian Steffens, M. Pesavento, M. Haardt","doi":"10.1109/SAM.2016.7569715","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569715","url":null,"abstract":"Exploiting the statistical properties of strictly non-circular (NC) signals in direction of arrival (DOA) estimation has long been an active area of research due to its associated performance improvements. Recently, this concept has been introduced to DOA estimation via sparse signal recovery (SSR), where similar benefits from processing NC signals are achieved. However, the standard approach to NC SSR requires solving a two-dimensional (2-D) SSR problem in the spatial and the phase rotation domain, which is not only associated with a high computational complexity itself but also with a 2-D off-grid problem. In this paper, we propose an entirely new NC SSR approach based on nuclear norm (rank) minimization after lifting the original bilinear optimization problem to a linear optimization problem in a higher-dimensional space. Thereby, the SSR-based 2-D estimation problem is reduced to a 1-D estimation problem only in the sampled spatial domain, which automatically provides gridless estimates of the rotation phases. In our second contribution, we present a simple closed-form grid offset estimator for a single NC source and a numerical joint grid offset estimation procedure for two closely-spaced NC sources assuming a uniform linear array (ULA). Simulations validate the effectiveness of the new approach.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"XXXIX 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131199781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Distributed and collaborative sound environment information extraction in binaural hearing aids 双耳助听器分布式协同声环境信息提取

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569708

R. Gil-Pita, Héctor A. Sánchez-Hevia, C. Llerena, Inma Mohino-Herranz, M. Utrilla-Manso, M. Rosa-Zurera

引用次数: 1

Comparison of comb and pulse train signal designs for active sonar 主动声纳梳状和脉冲序列信号设计的比较

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569636

Jonathan Soli, G. Hickman

引用次数: 3

Minimum BER precoding in 1-Bit massive MIMO systems 1位大规模MIMO系统的最小误码率预编码

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569655

H. Jedda, J. Nossek, A. Mezghani

引用次数: 73

Multi-microphone speech enhancement informed by auditory scene analysis 基于听觉场景分析的多麦克风语音增强

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569625

A. Plinge, S. Gannot

{"title":"Multi-microphone speech enhancement informed by auditory scene analysis","authors":"A. Plinge, S. Gannot","doi":"10.1109/SAM.2016.7569625","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569625","url":null,"abstract":"A multitude of multi-microphone speech enhancement methods is available. In this paper, we focus our attention to the well-known minimum variance distortionless response (MVDR) beamformer, due to its ability to preserve distortionless response towards the desired speaker while minimizing the output noise power. We explore two alternatives for constructing the steering vectors towards the desired speech source. One is only using the direct path of the speech propagation in the form of delay-only filters, while the other is using the entire room impulse response (RIR). All beamforming methods requires some control information to be able to accomplish the task of enhancing a desired speech signal. In this paper, an acoustic event detection method using biologically-inspired features is employed. It can interpret the auditory scene by detecting the presence of different auditory objects. This is employed to control the estimation procedures used by beamformer. The resulting system provides a blind method of speech enhancement that can improve intelligibility independently of any additional information. Experiments with real recordings show the practical applicability of the method. Significant gain in fwSNRseg is achieved. Compared to using the direct path only, the use of the entire RIR proves beneficial.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115694636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Low-complexity robust radar-embedded Sidelobe Level modulation using linear constrained optimization design 基于线性约束优化设计的低复杂度鲁棒雷达嵌入式旁瓣电平调制

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569664

Aline de Oliveira, R. Neto, J. Fortes

引用次数: 4

Enhanced block term decomposition for atrial activity extraction in atrial fibrillation ECG 增强块项分解用于心房颤动心电图心房活动提取

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569709

Lucas N. Ribeiro, A. D. Almeida, V. Zarzoso

{"title":"Enhanced block term decomposition for atrial activity extraction in atrial fibrillation ECG","authors":"Lucas N. Ribeiro, A. D. Almeida, V. Zarzoso","doi":"10.1109/SAM.2016.7569709","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569709","url":null,"abstract":"Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia but is still considered a challenging research subject since its electrophysiological mechanisms are not yet fully understood. Analyzing the atrial activity (AA) signal observed in surface electrocardiograms (ECG) is useful for clinical management and better understanding the propagation mechanisms inside the atria, but ventricular activity (VA) masks the AA in time and frequency domains. Signal processing techniques have been used to extract the AA signal. Blind Source Separation (BSS) methods can accomplish this task from multi-lead ECG. Recently, a deterministic tensor-based BSS method based on the Block Term Decomposition (BTD) was proposed and offered promising results in AA estimation. This method assumes that AF ECG leads can be expressed as linear combinations of damped exponential sources. However, QRST complexes of VA do not match this model, causing numerical issues. The present contribution proposes a Principal Component Analysis (PCA) preprocessing stage to attenuate the ventricular components. Experimental results show that this stage alleviates the ECG model mismatch, resulting in better AA estimation compared to competing methods and improved numerical properties compared to BTD without preprocessing.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122595837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

A novel algorithm for adapting the number of particles in particle filtering 粒子滤波中自适应粒子数的一种新算法

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569688

V. Elvira, J. Míguez, P. Djurić

引用次数: 3

Parallel low-complexity M-PSK detector for large-scale MIMO systems 大规模MIMO系统的并行低复杂度M-PSK检测器

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569705

Ganapati Hegde, Yang Yang, Christian Steffens, M. Pesavento

引用次数: 10

Sliding-window homotopy adaptive filter for estimation of sparse UWA channels 稀疏UWA信道估计的滑动窗口同伦自适应滤波器

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569608

Y. Zakharov, Jianghui Li

引用次数: 12