Stochastic reliable synchronization for coupled Markovian reaction–diffusion neural networks with actuator failures and generalized switching policies

Deqiang Zeng, Zhilin Pu, Ruimei Zhang, Shouming Zhong, Yajuan Liu and Guo-Cheng Wu

Applied Mathematics and Computation, 2019, vol. 357, issue C, 88-106

Abstract: This paper is concerned with the synchronization of coupled Markovian reaction–diffusion neural networks (RDNNs) with actuator failures and generalized switching policies (GSPs) via mode-dependent reliable control. Different from some existing results with all known transition rates, GSPs are considered for coupled Markovian RDNNs, where each transition rate can be completely unknown or only its estimation is known, or each transition rate of some modes is completely unknown. To reflect more realistic behaviors, actuator failures are considered for coupled Markovian RDNNs, and a mode-dependent reliable control scheme is proposed. Then, a new Lyapunov–Krasovskii functional (LKF) is introduced, which fully utilizes the information on the slope of neuron activation functions. Based on the LKF, a synchronization criterion is established in the form of linear matrix inequalities (LMIs). Moreover, the mode-dependent reliable control gains are obtained. Finally, a numerical example is given to verify the effectiveness of the proposed results.

Keywords: Mode-dependent reliable control; Coupled Markovian reaction–diffusion neural networks (RDNNs); Generalized switching policies (GSPs); Synchronization; Actuator failures (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:357:y:2019:i:c:p:88-106

DOI: 10.1016/j.amc.2019.03.055

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