Title :
Blind Separation and Equalization Using Novel Hill-Climbing Optimization
Author :
Xu, Dongxin ; Wu, Hsiao-Chun ; Chi, Chong-Yung
Author_Institution :
lnfoture, Inc., Boulder
Abstract :
In this paper, we construct a maximum-likelihood-equivalent metric or auxiliary function, which can result in a novel expectation-maximization Hill-Climbing (EM-HC) optimization procedure; it can be easily implemented for the estimation, detection and clustering applications since it is based on the simple auxiliary function. In this paper, one major application of our new EM-HC method, namely the blind separation and blind channel equalization, is presented and an efficient Iterative weighted least-mean squared (IWLMS) algorithm is derived thereupon. The new IWLMS algorithm derived from the EM-HC techniques greatly outperforms the prevalent blind equalization algorithm based on the constant-modulus criteria according to simulations.
Keywords :
blind equalisers; blind source separation; expectation-maximisation algorithm; least mean squares methods; blind channel equalization; blind separation; expectation-maximization Hill-Climbing optimization; iterative weighted least mean squared algorithm; maximum-likelihood- equivalent metric; Blind equalizers; Clustering algorithms; Digital communication; Hidden Markov models; Iterative algorithms; Maximum likelihood detection; Maximum likelihood estimation; Maximum likelihood linear regression; Signal processing algorithms; Speech recognition;
Conference_Titel :
Signals, Systems and Computers, 2007. ACSSC 2007. Conference Record of the Forty-First Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
978-1-4244-2109-1
Electronic_ISBN :
1058-6393
DOI :
10.1109/ACSSC.2007.4487154
