Adaptive FIR Filtering under Minimum Error/Input Information Criterion
نویسندگان
چکیده
Abstract: In this paper, we use the mutual information between error/input as the cost function for adaptive filtering. For the finite-impulse response (FIR) filter, the connections between the minimum error/input information (MEII) criterion and traditional mean-square error (MSE) criterion are investigated. We show that, for Gaussian case, the MEII criterion is equivalent to the well-known orthogonality condition. Based on the MEII criterion and kernel density estimation, we derive a stochastic gradient algorithm. Simulation results emphasize the effectiveness of this new algorithm.
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تاریخ انتشار 2008