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Finite/Fixed-Time Controls of Time-Varying Delayed Neural Networks in a Signed Graph

DOI: 10.12677/DSC.2024.131003, PP. 21-32

Keywords: 有限和固定时间控制,时变延迟,符号图,神经网络
Finite/Fixed-Time Controls
, Time-Varying Delayed, Signed Graph, Neural Networks

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In this paper, we explore the finite and fixed time controls of neural networks with time-varying delay in signed graphs. By designing finite and fixed time controllers and using matrix M defined in signed graph, stability theory and some other inequalities, the sufficient conditions and estimated time to achieve bipartite synchronization in finite and fixed time are obtained. Finally, a numerical example is given to verify the effectiveness of the designed finite and fixed time controllers.


[1]  Zhang, J., Zhang, A., Cao, J., et al. (2020) Adaptive Outer Synchronization between Two Delayed Oscillator Networks with Cross Couplings. Science China Information Sciences, 63, Article Number 209204.
[2]  He, S., Dai, S. and Dong, C. (2022) Adaptive Synchronization Control of Uncertain Multiple USVs with Prescribed Performance and Preserved Connectivity. Science China Information Sciences, 65, Article Number 199201.
[3]  Yu, J., Hu, C., Jiang, H., et al. (2014) Projective Synchronization for Fractional Neural Networks. Neural Networks, 49, 87-95.
[4]  Zhang, W., Li, C., Huang, T., et al. (2015) Synchronization of Neural Networks with Stochastic Perturbation via Aperiodically Intermittent Control. Neural Networks, 71, 105-111.
[5]  Zhu, S. and Bao, H. (2022) Event-Triggered Synchronization of Coupled Memristive Neural Networks. Applied Mathematics and Computation, 415, Article Number 126715.
[6]  Li, J., Jiang, H., Hu, C., et al. (2019) Finite/Fixed-Time Synchronization Control of Coupled Memristive Neural Networks. Journal of the Franklin Institute, 356, 9928-9952.
[7]  Chen, C., Li, L., Peng, H., et al. (2020) A New Fixed-Time Stability Theorem and Its Application to the Fixed-Time Synchronization of Neural Networks. Neural Networks, 123, 412-419.
[8]  Liu, X., Cao, J., Yu, W., et al. (2015) Nonsmooth Finite-Time Synchronization of Switched Coupled Neural Networks. IEEE Transactions on Cybernetics, 46, 2360-2371.
[9]  Sun, W., Guo, W., Li, B., et al. (2023) Finite/Fixed-Time Controls of Neural Networks in a Signed Graph. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 31 October 2023, 1-10.
[10]  Wu, H., Wang, X., Liu, X., et al. (2020) Finite/Fixed-Time Bipartite Synchronization of Coupled Delayed Neural Networks under a Unified Discontinuous Controller. Neural Processing Letters, 52, 1359-1376.
[11]  Hu, D., Tan, J., Shi, K., et al. (2022) Switching Synchronization of Reaction-Diffusion Neural Networks with Time- Varying Delays. Chaos, Solitons & Fractals, 155, Article Number 111766.
[12]  Zhang, H., Zhou, Y. and Zeng, Z. (2022) Master-Slave Synchronization of Neural Networks with Unbounded Delays via Adaptive Method. IEEE Transactions on Cybernetics, 53, 3277-3287.
[13]  He, W., Qian, F., Lam, J., et al. (2015) Quasi-Synchronization of Heterogeneous Dynamic Networks via Distributed Impulsive Control: Error Estimation, Optimization and Design. Automatica, 62, 249-262.
[14]  Guo, W., He, W., Sun, W., et al. (2022) Robust Finite-Time and Fixed-Time Bipartite Consensus Problems for Multi- Agent Systems via Discontinuous Protocol. International Journal of Control, 95, 380-389.
[15]  Meng, D., Du, M. and Jia, Y. (2016) Interval Bipartite Consensus of Networked Agents Associated with Signed Digraphs. IEEE Transactions on Automatic Control, 61, 3755-3770.
[16]  Wu, C.W. and Chua, L.O. (1995) Synchronization in an Array of Linearly Coupled Dynamical Systems. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 42, 430-447.
[17]  Bhat, S.P. and Bernstein, D.S. (2000) Finite-Time Stability of Continuous Autonomous Systems. SIAM Journal on Control and Optimization, 38, 751-766.


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