Blind identification and deconvolution for noisy two-input two-output channels

Authors:
Yuanqing Li;Andrzej Cichocki;Jianzhao Qin
Affiliations:
Institute for Infocomm Research, Singapore;Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute, Wako Shi, Saitama, Japan;Institute of Automation Science and Engineering, South China University of Technology, Guangzhou, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Year:
2005

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Abstract

This paper discusses blind identification and deconvolution of two-input two-output channels corrupted by noises based on secondorder statistics. First, the identifiability of channel is analyzed. By constructing an new criterion, the channel parameters can be identified precisely in the present of noises. Second, the cost function of identification is established and the corresponding algorithm is presented. Next, a feedback model is used for deconvolution, and several important problems, such as the effect of noises in the blind deconvolution of mixed sources and the stability of deconvolution model, are discussed. At last, simulation results are given to illustrate the theoretical results of this paper.