Performance study of Set-Membership NLMS algorithm over an adaptive incremental network

In this paper we apply Set-Membership (SM) adaptive algorithm over distributed networks based on incremental strategy. The distributed SM normalized least mean squares (dSM-NLMS) algorithm is introduced which has high convergence speed, low steady-state mean square error and low computational complexity features. The good performance of dSM-NLMS is demonstrated by several computer simulations in distributed networks.