State Estimation of Discrete-Time Fractional-Order Nonautonomous Neural Networks With Time Delays

Abstract

This article is dedicated to an investigation of state estimation for discrete-time fractional-order nonautonomous neural networks (DFNNNs) with leakage and discrete delays. To this end, some inequalities with more free parameters are obtained based on results related to nabla fractional difference, which considerably extend the existing results. In light of the effective estimator, some sufficient conditions to ensure the global asymptotic stability of the error system are obtained to solve the state estimation problem for DFNNNs by means of the linear matrix inequality (LMI) and the established inequalities. Finally, the theoretical results are verified by numerical simulations.