A Bayesian method for positive source separation

被引：0
|
作者：
Moussaoui, S [1 ]
Brie, D [1 ]
Caspary, O [1 ]
Mohammad-Djafari, A [1 ]
机构：
[1] UHP, CNRS, UMR 7039, CRAN, F-54506 Vandoeuvre Les Nancy, France
来源：
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年
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：
This paper considers the problem of source separation in the particular case where both the sources and the mixing coefficients are positive. The proposed method addresses the problem in a Bayesian framework. We assume a Gamma distribution for the spectra and the mixing coefficients. This prior distribution enforces the non-negativity. This leads to an original method for positive source separation. A simulation example is presented to illustrate the effectiveness of the method.
引用
收藏
页码：485 / 488
页数：4
相关论文
共 50 条
  • [1] Bayesian blind source separation of positive non stationary sources
    Ichir, MM
    Mohammad-Djafari, A
    BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, 2004, 735 : 493 - 500
  • [2] Variational Bayesian method for temporally correlated source separation
    Huang, Qinghua
    Yang, Jie
    Zhou, Yue
    NEURAL INFORMATION PROCESSING, PT 1, PROCEEDINGS, 2006, 4232 : 1058 - 1067
  • [3] On the decomposition of Mars hyperspectral data by ICA and Bayesian, positive source separation
    Moussaoui, S.
    Hauksdottir, H.
    Schmidt, F.
    Jutten, C.
    Chanussot, J.
    Brie, D.
    Doute, S.
    Benediktsson, J. A.
    NEUROCOMPUTING, 2008, 71 (10-12) : 2194 - 2208
  • [4] Mars hyperspectral data processing using ICA and Bayesian Positive Source Separation
    Hauksdottir, Hafrun
    Moussaoui, Said
    Schmidt, Frederic
    Jutten, Christian
    Chanussot, Jocelyn
    Brie, David
    BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, 2006, 872 : 113 - +
  • [5] Bayesian nonstationary source separation
    Huang, Qinghua
    Yang, Jie
    Zhou, Yue
    NEUROCOMPUTING, 2008, 71 (7-9) : 1714 - 1729
  • [6] A Bayesian approach to source separation
    Mohammad-Djafari, A
    BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, 2001, 567 : 221 - 244
  • [7] Bayesian source separation and localization
    Knuth, KH
    BAYESIAN INFERENCE FOR INVERSE PROBLEMS, 1998, 3459 : 147 - 158
  • [8] An Adaptive Bayesian Source Separation Method for Intensity Estimation of Facial AUs
    Mohammadi, Mohammad R.
    Fatemizadeh, Emad
    Mahoor, Mohammad H.
    IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, 2019, 10 (02) : 144 - 154
  • [9] A Bayesian Blind Source Separation Method for a Linear-quadratic Model
    Madrolle, Stephanie
    Duarte, Leonardo T.
    Grangeat, Pierre
    Jutten, Christian
    2018 26TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2018, : 1242 - 1246
  • [10] Bayesian source separation of fMRI signals
    Rowe, DB
    BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, PT 2, 2001, 568 : 375 - 387
12345