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| H∞ State Estimation of Delayed Memristive Neural Networks with Reaction-diffusion Terms |
| YU Pengfei, LIN Wenjuan
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| a. School of Automation; b. Shandong Key Laboratory of Industrial Control Technology, Qingdao University, Qingdao 266071, China |
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Abstract In order to obtain the state information of delayed memristive neural networks with reaction-diffusion terms more accurately, this paper designs a H∞ state estimator. Firstly, based on the Lyapunov-Krasovskii (L-K) functional method, a new delay-product-type augmented L-K functional is constructed to handle the effects of time-varying delays. Then, by utilizing techniques such as free-weight-matrix method, Wirtinger-based integral inequality, and extended reciprocally convex matrix inequality, further reduction in conservatism of the obtained results is achieved. Meanwhile, Dirichlet boundary conditions and Green formula, among others, are employed to address the reaction-diffusion terms of the system; finally, sufficient conditions for the global asymptotic stability of the error system that meet specific H∞ performance criteria are provided. Building upon this foundation, we present a design methodology for state estimator in terms of linear matrix inequalities. Finally, a numerical example is given to verify the effectiveness of the proposedH∞state estimator.
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Received: 29 March 2024
Published: 19 May 2026
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