A Fixed-Time Noise-Tolerance Neurodynamic Approach for Inverse Variational Inequalities

Abstract

A novel projection neurodynamic approach (PNA) possessed self-adaptive dynamic stepsize is proposed to deal with inverse variational inequality problems (IVIPs) in this paper. It is proved that the proposed PNA converges to the solution of the corresponding IVIPs within fixed-time under some mild conditions, and also proved that the convergence time upper bound of fixed-time neurodynamic approach does not depend on initial states. It is different from existing results with exponential convergence that the fixed-time range can be theoretically calculated. The proposed PNA has the advantage that they are all robust against bounded vanishing perturbations. Numerical simulation results expectably conform to the theoretical analysis of the proposed PNA.