Extended dissipative filtering for delayed Markov jump neural networks via adaptive event-triggered mechanism

Abstract

This paper concentrates the extended dissipative filtering problem for Markov jump neural networks with time delays. For resource-saving purpose, one effective way is to adopt an adaptive event-triggered mechanism. On the basis of Lyapunov method and matrix inequalities, an adequate condition, which ensuring the filtering error systems with the extended dissiaptivity, is developed. Then, by tackling a bunch of linear matrix inequalities, the design method of the desired filter parameters are established. Eventually, the filter design method is verified by an numerical example.