LEAST MEAN SQUARE METHOD FOR ESTIMATION IN SPARSE ADAPTIVE NETWORKS

摘要

The least mean square method for estimation in sparse adaptive networks is based on the Reweighted Zero Attracting Least Mean Square (RZA-LMS) algorithm, providing estimation for each node in the adaptive network. The extra penalty term of the RZA-LMS algorithm is then integrated into the Incremental LMS (ILMS) algorithm. Alternatively, the extra penalty term of the RZA-LMS algorithm may be integrated into the Diffusion LMS (DLMS) algorithm.