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Adaptive filtering under maximum mutual information criterion
- 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