Extended dissipativity of semi-Markov jump neural networks with partly unknown transition rates

In this paper, the synchronization problem is addressed for semi-Markov jump master-slave neural networks (SMJNN) with extended (X, Y, Z)-dissipativity performance and partly unknown transition rates (TR). Comparing with constant TR in Markovian jump neural networks, the TR of SMJNN depend on the sojourn time (ST) of semi-Markov process. First, some sufficient stability and extended (X, Y, Z)dissipativity criteria are established for the error system with partly unknown TR. Then, ST-dependent dissipativity criterion is transformed to feasible condition by the upper and lower bounds of TR. Furthermore, the state feedback controller is also designed to ensure the synchronization of SMJNN. Finally, a numerical example is provided to verify the admissibility and effectiveness of the acquired results. (c) 2020 Elsevier B.V. All rights reserved.

Automated summary

This paper addresses the synchronization problem for semi-Markov jump master-slave neural networks with extended dissipativity performance and partly unknown transition rates. Sufficient stability and dissipativity criteria are established, and a state feedback controller is designed to ensure synchronization. A numerical example is provided to verify the results.