哈尔滨工业大学学报（英文版）2007，Vol.14Issue(4)：518-523,6.
Single channel blind source separation based on ICA feature extraction
Single channel blind source separation based on ICA feature extraction
摘要
Abstract
A new technique is proposed to solve the blind source separation (BSS) given only a single channel observation. The basis functions and the density of the coefficients of source signals learned by ICA are used as the prior knowledge. Based on the learned prior information the learning rules of single channel BSS are presented by maximizing the joint log likelihood of the mixed sources to obtain source signals from single observation,in which the posterior density of the given measurements is maximized. The experimental results exhibit a successful separation performance for mixtures of speech and music signals.关键词
blind source separation (BSS)/ independent component analysis (ICA)/ single channel/ maximum likelihoodKey words
blind source separation (BSS)/ independent component analysis (ICA)/ single channel/ maximum likelihood分类
信息技术与安全科学引用本文复制引用
..Single channel blind source separation based on ICA feature extraction[J].哈尔滨工业大学学报（英文版）,2007,14(4):518-523,6.基金项目
Sponsored by the Research Foundation of Shanghai Municipal Education Commission( Grant No.06FZ012 and 06FZ028). （ Grant No.06FZ012 and 06FZ028）
