学术探索
学术期刊
新闻热点
数据分析
智能评审

Flexible independent component analysis

被引：92
作者：
Choi, S [1 ]
Cichocki, A
Amari, SI
机构：
[1] Chungbuk Natl Univ, Dept Elect Engn, Sch Elect & Elect Engn, Seoul, South Korea
[2] RIKEN, Brain Sci Inst, Brain Style Informat Syst Res Grp, Urawa, Saitama, Japan
[3] Warsaw Univ Technol, Inst Theory Elect Engn & Elect Measurements, PL-00661 Warsaw, Poland
来源：
JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY | 2000年 / 26卷 / 1-2期
关键词：
D O I：
10.1023/A:1008135131269
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper addresses an independent component analysis (ICA) learning algorithm with flexible nonlinearity, so named as flexible ICA, that is able to separate instantaneous mixtures of sub- and super-Gaussian source signals. In the framework of natural Riemannian gradient, we employ the parameterized generalized Gaussian density model for hypothesized source distributions. The nonlinear function in the flexible ICA algorithm is controlled by the Gaussian exponent according to the estimated kurtosis of demixing filter output. Computer simulation results and performance comparison with existing methods are presented.
引用
收藏
页码：25 / 38
页数：14
相关论文
共 41 条
[11]   BLIND BEAMFORMING FOR NON-GAUSSIAN SIGNALS [J].
CARDOSO, JF ;
SOULOUMIAC, A .
IEE PROCEEDINGS-F RADAR AND SIGNAL PROCESSING, 1993, 140 (06) :362-370
[12]   Equivariant adaptive source separation [J].
Cardoso, JF ;
Laheld, BH .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1996, 44 (12) :3017-3030
[13]   On the stability of source separation algorithms [J].
Cardoso, JF .
NEURAL NETWORKS FOR SIGNAL PROCESSING VIII, 1998, :13-22
[14]   Flexible independent component analysis [J].
Choi, S ;
Cichocki, A ;
Amari, S .
NEURAL NETWORKS FOR SIGNAL PROCESSING VIII, 1998, :83-92
[15]  
Choi S., 1999, J ELECT ENG INFORMAT, V4, P249
[16]  
CHOI S, 1999, 4 AS PAC C MED BIOL
[17]   A spurious equilibria-free learning algorithm for the blind separation of non-zero skewness signals [J].
Choi, SJ ;
Liu, RW ;
Cichocki, A .
NEURAL PROCESSING LETTERS, 1998, 7 (02) :61-68
[18]   A linear feedforward neural network with lateral feedback connections for blind source separation [J].
Choi, SJ ;
Cichocki, A .
PROCEEDINGS OF THE IEEE SIGNAL PROCESSING WORKSHOP ON HIGHER-ORDER STATISTICS, 1997, :349-353
[19]   Robust neural networks with on-line learning for blind identification and blind separation of sources [J].
Cichocki, A ;
Unbehauen, R .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 1996, 43 (11) :894-906
[20]   ROBUST LEARNING ALGORITHM FOR BLIND SEPARATION OF SIGNALS [J].
CICHOCKI, A ;
UNBEHAUEN, R ;
RUMMERT, E .
ELECTRONICS LETTERS, 1994, 30 (17) :1386-1387
12345