Approximate maximum likelihood source separation using the natural gradient

被引：6
|
作者：
Choi, S
Cichocki, A
Zhang, L
Amari, S
机构：
来源：
2001 IEEE THIRD WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, PROCEEDINGS | 2001年
关键词：
D O I：
10.1109/SPAWC.2001.923891
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper addresses a maximum likelihood approach to source separation in the case of overdetermined mixtures corrupted by additive white Gaussian noise. We present an objective function that is an approximate likelihood function based on the Laplace approximation. Then we derive a natural gradient adaptation algorithm which maximizes the corresponding approximate likelihood function. Useful behavior of the proposed method is verified by numerical experiments.
引用
收藏
页码：235 / 238
页数：4
相关论文
共 50 条
  • [41] Binaural source separation based on spatial cues and maximum likelihood model adaptation
    Abdipour, Roohollah
    Akbari, Ahmad
    Rahmani, Mohsen
    Nasersharif, Babak
    DIGITAL SIGNAL PROCESSING, 2015, 36 : 174 - 183
  • [42] Near field source separation improvement through unconditional maximum likelihood estimator
    Bonilla-Hernandez, Dario
    Covarrubias-Rosales, David H.
    Arceo-Olague, Jose G.
    IEEE Latin America Transactions, 2006, 4 (06) : 403 - 408
  • [43] ONLINE SPEECH SOURCE SEPARATION BASED ON MAXIMUM LIKELIHOOD OF LOCAL GAUSSIAN MODELING
    Togami, Masahito
    2011 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2011, : 213 - 216
  • [44] Maximum likelihood blind source separation: A context-sensitive generalization of ICA
    Pearlmutter, BA
    Parra, LC
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 9: PROCEEDINGS OF THE 1996 CONFERENCE, 1997, 9 : 613 - 619
  • [45] Natural gradient multichannel blind deconvolution and source separation using causal FIR filters
    Douglas, SC
    Sawada, H
    Makino, S
    2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL V, PROCEEDINGS: DESIGN AND IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS INDUSTRY TECHNOLOGY TRACKS MACHINE LEARNING FOR SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING SIGNAL PROCESSING FOR EDUCATION, 2004, : 477 - 480
  • [46] A Modified Natural Gradient Algorithm for Blind Source Separation Using Generalized Constant Modulus
    Gu, Fanglin
    Zhang, Hang
    Zhang, Jiang
    Zhu, Desheng
    Luo, Pan
    2013 36TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP), 2013, : 663 - 666
  • [47] Using piecewise linear nonlinearities in the natural gradient and fastICA algorithms for blind source separation
    Chao, Jih-Cheng
    Douglas, Scott C.
    2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12, 2008, : 1813 - +
  • [48] Approximate maximum likelihood estimation of the Bingham distribution
    Bee, Marco
    Benedetti, Roberto
    Espa, Giuseppe
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2017, 108 : 84 - 96
  • [49] APPROXIMATE MAXIMUM-LIKELIHOOD FREQUENCY ESTIMATION
    STOICA, P
    HANDEL, P
    SODERSTROM, T
    AUTOMATICA, 1994, 30 (01) : 131 - 145
  • [50] Exact and approximate maximum likelihood localization algorithms
    Chan, YT
    Hang, HYC
    Ching, PC
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2006, 55 (01) : 10 - 16
12345