摘要

Among the existing strategies over adaptive networks, the tap-length of an unknown parameter vector is assumed to be known a prior and constant, thus they are not suitable in the context where the optimal tap-length is unknown or variable. We therefore propose a spatially distributed variable tap-length algorithm over adaptive networks, based on the rule of least mean square error of the entire network. In the approach, the data of the network diffuse across the nodes through local iterations between the nodes and their neighbors, thus the accuracy is guaranteed, while only a small computation is required. Simulations show that the proposed strategy is effective to track and estimate the parameter vector of interest in terms of tap-length and weights.

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