Frequency-domain separation algorithms for instantaneous mixtures

被引：0
|
作者：
Mei, TM [1 ]
Yin, FL
机构：
[1] Dalian Univ Technol, Sch Elect & Informat, Dalian 116023, Peoples R China
[2] Shenyang Inst Technol, Sch Informat Engn, Shenyang 110168, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2004, PT 1 | 2004年 / 3173卷
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 this paper, we proposed algorithms for the blind separation of instantaneous mixtures in frequency domain. They are based on the joint diagonalization of power spectral density matrices. These algorithms are suitable for both stationary and nonstationary but temporally colored sources. Simulation results show that the new algorithms are of high separation performance.
引用
收藏
页码：666 / 671
页数：6
相关论文
共 50 条
  • [1] Frequency-domain contrast functions for separation of convolutive mixtures
    Pesquet, JC
    Chen, BN
    Petropulu, AP
    [J]. 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 - VOL IV: SIGNAL PROCESSING FOR COMMUNICATIONS; VOL V: SIGNAL PROCESSING EDUCATION SENSOR ARRAY & MULTICHANNEL SIGNAL PROCESSING AUDIO & ELECTROACOUSTICS; VOL VI: SIGNAL PROCESSING THEORY & METHODS STUDENT FORUM, 2001, : 2765 - 2768
  • [2] Equivalence between frequency-domain blind source separation and frequency-domain adaptive beamforming for convolutive mixtures
    Araki, S
    Makino, S
    Hinamoto, Y
    Mukai, R
    Nishikawa, T
    Saruwatari, H
    [J]. EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING, 2003, 2003 (11) : 1157 - 1166
  • [3] Equivalence between Frequency-Domain Blind Source Separation and Frequency-Domain Adaptive Beamforming for Convolutive Mixtures
    Shoko Araki
    Shoji Makino
    Yoichi Hinamoto
    Ryo Mukai
    Tsuyoki Nishikawa
    Hiroshi Saruwatari
    [J]. EURASIP Journal on Advances in Signal Processing, 2003
  • [4] Separation of convolutive mixtures in the frequency-domain using only two frequency bins
    Dapena, A
    Serviere, C
    Castedo, L
    [J]. 2002 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-IV, PROCEEDINGS, 2002, : 1633 - 1636
  • [5] A New Initialization Method for Frequency-Domain Blind Source Separation Algorithms
    Clark, Felipe S. P.
    Petraglia, Mariane R.
    Haddad, Diego B.
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2011, 18 (06) : 343 - 346
  • [6] A Time–Frequency Domain Blind Source Separation Method for Underdetermined Instantaneous Mixtures
    Tianliang Peng
    Yang Chen
    Zengli Liu
    [J]. Circuits, Systems, and Signal Processing, 2015, 34 : 3883 - 3895
  • [7] A novel method for permutation correction in frequency-domain in blind separation of speech mixtures
    Serviere, C
    Pham, DT
    [J]. INDEPENDENT COMPONENT ANALYSIS AND BLIND SIGNAL SEPARATION, 2004, 3195 : 807 - 815
  • [8] Frequency-domain implementation of a time-domain blind separation algorithm for convolutive mixtures of sources
    Ohata, Masashi
    Matsuoka, Kiyotoshi
    [J]. INDEPENDENT COMPONENT ANALYSIS AND SIGNAL SEPARATION, PROCEEDINGS, 2007, 4666 : 528 - +
  • [9] Blind separation of linear instantaneous mixtures of non-stationary signals in the frequency domain
    Hosseini, Shahram
    Deville, Yannick
    Saylani, Hicham
    [J]. SIGNAL PROCESSING, 2009, 89 (05) : 819 - 830
  • [10] A Time-Frequency Domain Blind Source Separation Method for Underdetermined Instantaneous Mixtures
    Peng, Tianliang
    Chen, Yang
    Liu, Zengli
    [J]. CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2015, 34 (12) : 3883 - 3895
12345