Fixed-Time Synchronization of Reaction-Diffusion Fuzzy Neural Networks with Stochastic Perturbations

Hayrengul Sadik, Abdujelil Abdurahman () and Rukeya Tohti
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Hayrengul Sadik: College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China
Abdujelil Abdurahman: College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China
Rukeya Tohti: College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China

Mathematics, 2023, vol. 11, issue 6, 1-15

Abstract: In this paper, we investigated the fixed-time synchronization problem of a type of reaction-diffusion fuzzy neural networks with stochastic perturbations by developing simple control schemes. First, some generalized fixed-time stability results are introduced for stochastic nonlinear systems. Based on these results, some generic fixed-time stability criteria are established and upper bounds of settling time are directly calculated by using several special functions. Then, the fixed-time synchronization of a type of reaction-diffusion fuzzy neural networks with stochastic perturbations is analysed by designing a type of controller which is more simple and thus have a better applicability. Finally, one numerical example with its Matlab simulations is provided to show the feasibility of developed theoretical results.

Keywords: fixed-time synchronization; reaction-diffusion term; stochastic perturbation; fuzzy neural network (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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