Multichannel blind deconvolution using a novel filter decomposition method

被引:0
|
作者
Xia, Bin [1 ]
Zhang, Liqing [1 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Comp Sci & Engn, Shanghai 200030, Peoples R China
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In our previous work [111, we introduced a filter decomposition method for blind deconvolution in non-minimum phase system. To simplify the deconvolution procedure, we further study the demixing filter and modify the cascade structure of demixing filter. In this paper, we introduce a novel two-stage algorithm for blind deconvolution. In first stage, we present a permutable cascade structure which constructed by a causal filter and an anti-causal scalar filter. Then, we develop SOS-based algorithm for causal filter and derive a natural gradient algorithm for anti-causal scalar filter. At second stage, we apply an instantaneous ICA algorithm to eliminate the residual instantaneous mixtures. Computer simulations show the validity and effectiveness of this approach.
引用
收藏
页码:1202 / 1207
页数:6
相关论文
共 50 条
  • [11] Multichannel Blind Deconvolution using Low Rank Recovery
    Romberg, Justin
    Tian, Ning
    Sabra, Karim
    INDEPENDENT COMPONENT ANALYSES, COMPRESSIVE SAMPLING, WAVELETS, NEURAL NET, BIOSYSTEMS, AND NANOENGINEERING XI, 2013, 8750
  • [12] Multichannel blind seismic deconvolution using dynamic programming
    Heimer, Alon
    Cohen, Israel
    SIGNAL PROCESSING, 2008, 88 (07) : 1839 - 1851
  • [13] ITERATIVE MULTICHANNEL BLIND DECONVOLUTION METHOD FOR TEMPORALLY COLORED SOURCES
    Zhang Mingjian Wei Gang(School of Electronics and Information
    Journal of Electronics(China), 2004, (03) : 243 - 248
  • [14] ITERATIVE MULTICHANNEL BLIND DECONVOLUTION METHOD FOR TEMPORALLY COLORED SOURCES
    Zhang Mingjian Wei GangSchool of Electronics and Information South China University of Technology Guangzhou
    JournalofElectronics, 2004, (03) : 243 - 248
  • [15] Adaptive paraunitary filter banks for contrast-based multichannel blind deconvolution
    Sun, X
    Douglas, SC
    2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS: VOL I: SPEECH PROCESSING 1; VOL II: SPEECH PROCESSING 2 IND TECHNOL TRACK DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS NEURALNETWORKS FOR SIGNAL PROCESSING; VOL III: IMAGE & MULTIDIMENSIONAL SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING, 2001, : 2753 - 2756
  • [16] Blind multichannel identification based on Kalman filter and eigenvalue decomposition
    Tiemin Mei
    International Journal of Speech Technology, 2019, 22 : 1 - 11
  • [17] Blind multichannel identification based on Kalman filter and eigenvalue decomposition
    Mei, Tiemin
    INTERNATIONAL JOURNAL OF SPEECH TECHNOLOGY, 2019, 22 (01) : 1 - 11
  • [18] Multichannel blind signal deconvolution using high order statistics
    Moreau, E
    Thirion, N
    8TH IEEE SIGNAL PROCESSING WORKSHOP ON STATISTICAL SIGNAL AND ARRAY PROCESSING, PROCEEDINGS, 1996, : 336 - 339
  • [19] Adaptive Regularized Multichannel Blind Deconvolution Using Alternating Minimization
    James, Soniya
    Maik, Vivek
    Paik, Joonki
    2015 IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE (IACC), 2015, : 1163 - 1168
  • [20] Multichannel seismic deconvolution using Bayesian method
    1600, International Frequency Sensor Association, 46 Thorny Vineway, Toronto, ON M2J 4J2, Canada (159):