New fuzzy zeroing neural network with noise suppression capability for time-varying linear equation solving

Abstract

Recently, the zeroing neural network (ZNN) with continuous/discrete-time forms has realized success in solving the time-varying linear equation (TVLE). In this paper, we provide a further investigation by proposing a new fuzzy zeroing neural network (FZNN) model to solve the TVLE in noisy environment. Such a FZNN model, which has the capability of suppressing noise, is developed by using the integration enhancement and fuzzy control strategy. Then, theoretical analysis is presented to show that the proposed FZNN model can effectively solve the TVLE, even with the existence of noise. Comparative simulation results through different examples further verify the effectiveness and robustness of the proposed FZNN model on TVLE solving.