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Constrained adaptive filtering algorithms have been extensively studied in many applications. Most existing constrained adaptive filtering algorithms are developed under the mean square error (MSE) criterion, which is an ideal optimality criterion under Gaussian noises. This assumption however fails to model the behavior of non-Gaussian noises found in practice. Motivated by the robustness and simplicity...
A diffusion general mixed-norm (DGMN) algorithm for distributed estimation over network (DEoN) is proposed. The standard diffusion adaptive filtering algorithm with a single error norm exhibits slow convergence speed and poor misadjustments under specific environments. To overcome this drawback, the DGMN is developed by using a convex mixture of p and textit q norms as the cost function to improve...
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