A Blind Source Separation Method Based on Kalman Filtering

被引：3
|
作者：
Hu, Zhihui [1 ]
Feng, Jiuchao [1 ]
机构：
[1] S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, CIRCUITS AND SYSTEMS PROCEEDINGS, VOLUMES I & II: COMMUNICATIONS, NETWORKS AND SIGNAL PROCESSING, VOL I/ELECTRONIC DEVICES, CIRUITS AND SYSTEMS, VOL II | 2009年
关键词：
CHAOTIC SIGNAL; EXTRACTION;
D O I：
10.1109/ICCCAS.2009.5250473
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
According to Nonlinear Principal Component Analysis (NPCA) criterion, a blind source separation algorithm based on Kalman filtering is proposed in this paper. The convergence property of the algorithm is analyzed. The performance of the algorithm is evaluated by using several different kinds of sources. The effect of the number of iteration steps and the observation noise for the performance are investigated. The results show that this algorithm can separate chaotic as well as other sources from linear instantaneous mixtures effectively.
引用
收藏
页码：473 / 476
页数：4
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