MMN-4028
State estimation of memristor-based stochastic neural networks with mixed variable delays
Ramasamy Saravanakumar; Hemen Dutta;Abstract
In this paper, the state estimation problem for memristorbased stochastic neural networks (MSNNs) with mixed variable delays is studied. By establishing a new Lyapunov-Krasovskii functional (LKFs) with quadruple integral terms, and using linear matrix inequality technique, asymptotic stability conditions are established for the estimation error system. The estimator gain can be obtained by solving linear matrix inequalities. Numerical simulations are given to demonstrate the effectiveness and superiority of the new scheme.
Vol. 24 (2023), No. 3, pp. 1495-1513
DOI: 10.18514/MMN.2023.4028