A New Least Mean Squares Adaptive Algorithm over Distributed Networks Based on Incremental Strategy
نویسندگان
چکیده
This paper applies the new least mean squares (LMS) adaptive algorithm, which is circulantly weighted LMS (CLMS), in distributed networks based on incremental strategy. Thedistributed CLMS (dCLMS) algorithm is optimized with respect to approximate a priori knowledge of input autocorrelation signals from all nodes in the network. In comparison with dLMS, the dCLMS adaptive algorithm has faster convergence speed especially for highly colored input signals. We demonstrate the good performance of dCLMS through several simulation results in distributed networks.
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تاریخ انتشار 2015