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Adaptive filtering under maximum mutual information criterion

Authors :
Chen, Badong
Hu, Jinchun
Li, Hongbo
Sun, Zengqi
Source :
Neurocomputing. Oct2008, Vol. 71 Issue 16-18, p3680-3684. 5p.
Publication Year :
2008

Abstract

Abstract: The maximum mutual information (MaxMI) criterion is used as the adaptation cost for the adaptive filtering. This criterion is robust to measure distortions, and has strong connection with traditional mean-square error (MSE) criterion. Under Gaussian assumption, the closed-form solution of the finite impulse response (FIR) filter is obtained. Further, based on the kernel density estimation, the stochastic mutual information gradient (SMIG) algorithm is derived. Simulation results emphasize the robustness of this new algorithm. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
09252312
Volume :
71
Issue :
16-18
Database :
Academic Search Index
Journal :
Neurocomputing
Publication Type :
Academic Journal
Accession number :
34296846
Full Text :
https://doi.org/10.1016/j.neucom.2008.02.003