Robust channel identification using FOCUSS method

Zhaoshui He, Andrzej Cichocki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Blind channel identification can be cast into a single-input-multi-output (SIMO) identification problem by oversampling and then solved easily by SIMO identification methods. Due to this, SIMO identification is of great interest and attracts a lot of attention in the past twenty years. Many efficient methods have been developed for this problem. However, most of them are sensitive to overestimation of channel order. Based on sparse representation, an efficient SIMO identification method is proposed in this paper. Differing from the Prediction Error Method, the new algorithm does not require the input signal to be independent and identical distribution, and even the input signal can be non-stationary. In addition, the new algorithm is more robust to the overestimation of channel order.

Original languageEnglish
Title of host publicationAdvances in Neural Network Research and Applications
Number of pages7
Publication statusPublished - 2010
Externally publishedYes
Event7th International Symposium on Neural Networks, ISNN 2010 - Shanghai, China
Duration: 6 Jun 20109 Jun 2010

Publication series

NameLecture Notes in Electrical Engineering
Volume67 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


Conference7th International Symposium on Neural Networks, ISNN 2010


  • Blind identification
  • FOCUSS algorithm
  • Single input multiple output

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