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In this paper, an adaptive filtering algorithm, termed the extended kernel recursive maximum correntropy (EX-KRMC) algorithm is proposed as a novel approach of traditional recursion based adaptive filtering algorithms. Maximum correntropy criterion is employed to better the robustness to non-Gaussian noise and kernel methods are used to enable the capacity for nonlinear systems. It is verified by...
Information-theoretic cost functions such as minimization of the error entropy (MEE) can extract more structure from the error signal, yielding better results in many realistic problems. However, adaptive filters (AFs) using MEE methods are more computationally intensive when compared to conventional, mean-squared error (MSE) methods employed in the well-known, least mean squares (LMS) algorithm....
Techniques for the power efficient data path synthesis of sum-of-products computations between data and coefficients are presented. The proposed techniques exploit specific features of this type of computations. Efficient heuristics for the scheduling and assignment tasks, based on the concept of the Traveling Salesman's Problem, are described. Different cost functions are proposed to drive the synthesis...
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