Bounded real lemmas and exponential Hoo control for memristor-based neural networks with unbounded time-varying delays

This paper focuses on developing a bounded real lemma (BRL) and designing a state-feedback controller which guarantees a prescribed Hoo performance level for a class of memristor-based neural networks (MNNs) with unbounded time-varying delays. Firstly, a BRL for MNNs is presented by taking a new approach based on system solutions. This approach requires neither transformation of the model nor construction of Lyapunov-Krasovskii functionals, thereby reducing computational effort and complexity. In addition, the obtained BRL contains only a few simple inequalities, which can be easily solved by using MATLAB. Secondly, the condition for the existence of exponential Hoo controller is given based on the obtained BRL. Finally, two simulation examples demonstrate the validity of the theoretical results. (c) 2023 Published by Elsevier B.V. on behalf of International Association for Mathematics and Computers in Simulation (IMACS).