计算机工程与应用Issue(8)：206-208,3.DOI:10.3778/j.issn.1002-8331.1203-0091
一种基于NPCA的自适应变步长盲源分离算法
摘要
Abstract
It is well known that the convergence rate and steady-error are crucial performance indexes for sequential Blind Source Separation(BSS)algorithms. In order to speed up the convergence rate and improve tracking ability, it proposes a novel adaptive step-size BSS algorithm based on Nonlinear Principal Component Analysis(NPCA). The proposed algorithm utilizes an adaptive step-size whose value is adjusted in sympathy with the time-varying dynamics of the input signals and the separating ma-trix. Simulation results show that the proposed algorithm has faster convergence rate and better tracking ability compared with existed NPCA algorithm.关键词
盲源分离/自适应变步长/非线性主成分分析Key words
blind source separation/adaptive step-size/nonlinear principal component analysis分类
信息技术与安全科学引用本文复制引用
蒋照菁,辜方林,张杭..一种基于NPCA的自适应变步长盲源分离算法[J].计算机工程与应用,2013,(8):206-208,3.基金项目
国家自然科学基金青年科学基金项目(No.61001106) （No.61001106）
