Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
410796 | Neurocomputing | 2008 | 5 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Badong Chen, Jinchun Hu, Hongbo Li, Zengqi Sun,