Reachable set estimation of delayed Markovian jump neural networks based on an augmented zero equality approach

Abstract

AbstractThis article suggests the methods to estimate the reachable set of Markovian jump neural networks (MJNNs) with time‐varying delays. By building up improved Lyapunov–Krasovskii functionals, the conditions that have less conservatism for the delay‐dependent can be obtained. Integral inequalities are employed to estimate the reachable set of MJNNs, resulting in more effective and conservative outcomes regarding time delays. Moreover, some mathematical techniques, the augmented zero equality approach, improve the results and eliminated the free variables. Two numerical examples and figures demonstrated that the proposed method was effective and provided less conservative results than previous research.