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Singh S, Kumar U, Das S, Alsaadi F, Cao J. Synchronization of Quaternion Valued Neural Networks with Mixed Time Delays Using Lyapunov Function Method. Neural Process Lett 2021. [DOI: 10.1007/s11063-021-10657-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Zhang T, Jian J. New results on synchronization for second-order fuzzy memristive neural networks with time-varying and infinite distributed delays. Knowl Based Syst 2021. [DOI: 10.1016/j.knosys.2021.107397] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Wang Z, Cui W, Jin W. Finite-time synchronization for fuzzy inertial cellular neural networks with time-varying delays via integral inequality. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021. [DOI: 10.3233/jifs-211065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
This paper mainly considers the finite-time synchronization problem of fuzzy inertial cellular neural networks (FICNNs) with time-varying delays. By constructing the suitable Lyapunov functional, and using integral inequality techniques, several sufficient criteria have been proposed to ensure the finite-time synchronization for the addressed (FICNNs). Without applying the known finite-time stability theorem, which is widely used to solve the finite-time synchronization problems for (FICNNs). In this paper, the proposed method is relatively convenient to solve finite-time synchronization problem of the addressed system, this paper extends the research works on the finite-time synchronization of (FICNNs). Finally, numerical simulations illustrated verify the effectiveness of the proposed results.
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Affiliation(s)
- Zhenjie Wang
- School of Mathematics Physics and Statistics, Shanghai University of Engineering Science, Shanghai, PR China
| | - Wenxia Cui
- School of Mathematics Physics and Statistics, Shanghai University of Engineering Science, Shanghai, PR China
| | - Wenbin Jin
- School of Mathematics Physics and Statistics, Shanghai University of Engineering Science, Shanghai, PR China
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Abdelaziz M, Chérif F. Exponential Lag Synchronization and Global Dissipativity for Delayed Fuzzy Cohen–Grossberg Neural Networks with Discontinuous Activations. Neural Process Lett 2020. [DOI: 10.1007/s11063-019-10169-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Li C, Gao X. One-layer neural network for solving least absolute deviation problem with box and equality constraints. Neurocomputing 2019. [DOI: 10.1016/j.neucom.2018.11.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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