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State Estimation for Complex-Valued Inertial Neural Networks with Multiple Time Delays. MATHEMATICS 2022. [DOI: 10.3390/math10101725] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
In this paper, the problem of state estimation for complex-valued inertial neural networks with leakage, additive and distributed delays is considered. By means of the Lyapunov–Krasovskii functional method, the Jensen inequality, and the reciprocally convex approach, a delay-dependent criterion based on linear matrix inequalities (LMIs) is derived. At the same time, the network state is estimated by observing the output measurements to ensure the global asymptotic stability of the error system. Finally, two examples are given to verify the effectiveness of the proposed method.
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Wu KN, Ren MZ, Liu XZ. Exponential input-to-state stability of stochastic delay reaction–diffusion neural networks. Neurocomputing 2020. [DOI: 10.1016/j.neucom.2019.09.118] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Zhou Z, Liao H, Zhang Z. Global asymptotic stability for discrete-time Cohen-Grossberg neural networks with delays by combining graph theoretic approach with Homeomorphism concept. J EXP THEOR ARTIF IN 2020. [DOI: 10.1080/0952813x.2020.1801854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Zheng Zhou
- School of Applied Mathematics, Xiamen University of Technology, Xiamen, China
| | - Huaying Liao
- Department of Mathematics and Computer Science, Nanchang Normal University, Nanchang, China
| | - Zhengqiu Zhang
- College of Mathematics and Econometrics, Hunan University, Changsha, China
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Zeng Y, Xiao L, Li K, Li J, Li K, Jian Z. Design and analysis of three nonlinearly activated ZNN models for solving time-varying linear matrix inequalities in finite time. Neurocomputing 2020. [DOI: 10.1016/j.neucom.2020.01.070] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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He D, Zhou B, Zhang Z. Novel Sufficient Conditions on Periodic Solutions for Discrete-Time Neutral-Type Neural Networks. Neural Process Lett 2020. [DOI: 10.1007/s11063-019-10066-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Finite-time synchronization for delayed complex-valued neural networks via integrating inequality method. Neurocomputing 2018. [DOI: 10.1016/j.neucom.2018.08.063] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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