Resilient memory sampled-data controller for synchronization of semi-Markovian jump competitive neural networks with mixed delays

The primary aim of this paper is to design a resilient controller to ensure the synchronization of semi-Markovian jump competitive neural networks with mixed delays, which include discrete time-varying delay, leakage delay and distributed time-varying delay. To facilitate this, two-sided looped-type Lyapunov–Krasovskii functionals (LKFs) are utilized as a systematic approach for analyzing the synchronization of the system. By applying an innovative integral inequality technique based on free weighting matrices, this study establishes sufficient conditions for ensuring synchronization. A central contribution of this work is the development and implementation of a resilient memory sampled-data control mechanism, that is essential for achieving synchronization of the proposed system. This controller effectively mitigates the impact of input delays, sampling errors and external disturbances, ensuring robust performance even in the presence of uncertainties. The synchronization criteria are derived in terms of linear matrix inequalities (LMIs). The proposed method is verified through numerical simulations and the outcomes are graphically illustrated, demonstrating the efficacy of the resilient memory sampled-data controller.