电子科技大学学报2017，Vol.46Issue(2)：352-356,5.DOI:10.3969/j.issn.1001-0548.2017.02.006
多类型噪声中的独立成分分离算法
Algorithm of Independent Component Analysis for Multi-Types Noise Moments
摘要
Abstract
The performance of fast fixed-point algorithm of independent component analysis (ICA) is influenced by noise significantly. However, the method of noisy ICA proposed by Hyv?rinen did not discuss the impulsive noise. In this study, we extend the algorithm proposed by Hyv?rinen for noisy ICA to the more general situation in which the signals are observed in the presence of Gaussian and impulsive noise. We use the non-polynomial function to analyze the impulsive noise, which is to guarantee the impulsive noise can be distinguished from the observed data. Furthermore, combined with the noisy ICA method, a modification to the algorithm for multi-noise is introduced. The proposed technique improves the performance of Hyv?rinen's algorithm for cases where the observed signals contain Gaussian and impulsive noise. We also perform simulations to demonstrate the effectiveness of the proposed method.关键词
独立成分分析/多维信号处理/噪声/噪声算法Key words
independent component analysis/multidimensional signal processing/noise/noisy algorithm分类
信息技术与安全科学引用本文复制引用
冯平兴,魏平..多类型噪声中的独立成分分离算法[J].电子科技大学学报,2017,46(2):352-356,5.基金项目
国家自然科学基金(11176005) （11176005）
