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This work examines the mean-square error performance of diffusion stochastic algorithms under a generalized coordinate-descent scheme. In this setting, the adaptation step by each agent is limited to a random subset of the coordinates of its stochastic gradient vector. The selection of which coordinates to use varies randomly from iteration to iteration and from agent to agent across the network....
The proportionate normalized least-mean-square (PNLMS) algorithm with individual activation factors (IAFPNLMS) converges fast when the echo path is highly sparse, and has been used in system identification. Unfortunately, it suffers from slow convergence speed after the fast initial process. To solve the problem, in this paper, the idea of mu-law PNLMS (MPNLMS) algorithm is introduced into the IAFPNLMS...
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