盲信号分离

电子学报 ›› 2001, Vol. 29 ›› Issue (S1): 1766-1771.

盲信号分离

张贤达, 保铮

西安电子科技大学雷达信号处理重点实验室, 陕西西安, 710071

收稿日期:2001-06-11 修回日期:2001-09-20 出版日期:2001-12-25
- 作者简介:
- 张贤达 男.1946年出生于江西省.现任西安电子科技大学特聘教授(教育部"长江学者"奖励计划)和博士生导师,并任清华大学教授和博士生导师.研究方向为信号处理及其在雷达和通信中的应用.曾获国家自然科学奖1项、部级科技进步奖2项及国防发明专利1项.已发表论文80余篇,其中IEEE汇刊22篇(含正式录用),出版学术专著5部:《现代信号处理》、《时间序列分析-高阶统计量方法》、《信号处理中的线性代数》、《非平稳信号分析与处理》以及《通信信号处理》. 保铮男.1927年出生于江苏省.教授,博士生导师,中国科学院院士,中国电子科学学会会士.研究领域为雷达信号处理及现代信号处理.
- 基金资助:
- 国家自然科学基金资助项目 (No.60072043)

Blind Source Separation

ZHANG Xian-da, BAO Zheng

Key Laboratory for Radar Signal Processing, Xidian University, Xi'an, Shanxi 710071, China

Received:2001-06-11 Revised:2001-09-20 Online:2001-12-25 Published:2001-12-25

摘要/Abstract

摘要： 阵列处理和数据分析的一个典型问题是从混合的观测数据向量中恢复不可观测的各个源信号.盲信号分离是解决这一问题的一门新技术,近几年吸引了信号处理学界和神经网络学界众多学者的研究兴趣.本文将以独立分量分析和非线性主分量分析为主要对象,综述盲信号分离技术的理论、方法及应用等方面的发展,并作有关展望.

关键词: 信号分离, 神经网络, 独立分量分析, 主分量分析

Abstract: A typical problem in array processing and data analysis is to recover the unobserved source signals from their mixtures.Blind source separation(BSS) is a powerful methodology for solving this problem.In recent years,the BSS has received considerable attention from the signal processing community and the neural network community.This paper presents a survey and review on the BSS,focusing on the independent component analysis(ICA) and the principal component analysis(PCA).

Key words: source separation, neural network, independent component analysis, principal component analysis

中图分类号:

TN911.23

张贤达, 保铮. 盲信号分离[J]. 电子学报, 2001, 29(S1): 1766-1771.

ZHANG Xian-da, BAO Zheng . Blind Source Separation[J]. Acta Electronica Sinica, 2001, 29(S1): 1766-1771.

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