标题:A fast blind source separation algorithm for binaural hearing AIDS based on frequency bin selection
作者:Liu, Baiyun ;Wei, Ying
作者机构:[Liu, B] School of Information Science and Engineering, Shandong University, Qingdao, China;[ Wei, Y] School of Control Science and Engineering, Shand 更多
会议名称:23rd IEEE International Conference on Digital Signal Processing, DSP 2018
会议日期:19 November 2018 through 21 November 2018
来源:International Conference on Digital Signal Processing, DSP
出版年:2019
卷:2018-November
DOI:10.1109/ICDSP.2018.8631688
关键词:covariance matrix determinant; frequency bin selection; outlier detection
摘要:In binaural signal processing, due to the large distance between two ears, spatial aliasing occurs at the high frequencies. Therefore, the fast algorithms based on frequency bin selection usually limit the frequency range to below 1kHz to avoid dealing with the aliasing problem. In this paper, a fast Blind Source Separation (BSS) algorithm based on frequency bin selection without limiting the range of frequency bin selection was proposed. Efficient method was used to estimate the propagation model parameters to solve the inaccurate delay problem and permutation ambiguity. Besides, we used outlier detection method to further remove frequency bins with poor separation performance after the first selection, which ensures the accuracy of the normalized attenuation and delay matrices. Simulation results show that the proposed algorithm reduces computational complexity and improves separation performance compared with limited range frequency bin selection BSS. © 2018 IEEE.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062782267&doi=10.1109%2fICDSP.2018.8631688&partnerID=40&md5=94378e2b945f0723bd750688b716bfc4
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