Finite-Time and Fixed-Time Synchronization of Complex-Valued Recurrent Neural Networks with Discontinuous Activations and Time-Varying Delays

This paper focuses on the finite-time synchronization analysis for complex-valued recurrent neural networks with time delays. First, two kinds of common activation functions appearing in the existing references are combined together and more general assumptions are given. To achieve our aim, a nonlinear delayed controller with two independent parameters different from the existing ones is provided, which leads to great difficulty. To overcome it, a newly developed inequality is used. Then, via Lyapunov function approach, some criteria are derived to guarantee the finite-time synchronization of the considered system, and the settling time for synchronization is also estimated. Finally, two numerical simulations are given to support the effectiveness and advantages of the obtained results.

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Controller design for finite-time and fixed-time stabilization of fractional-order memristive complex-valued BAM neural networks with uncertain parameters and time-varying delays

Neural Networks ◽

10.1016/j.neunet.2020.06.021 ◽

2020 ◽

Vol 130 ◽

pp. 60-74 ◽

Cited By ~ 1

Author(s):

Emel Arslan ◽

G. Narayanan ◽

M. Syed Ali ◽

Sabri Arik ◽

Sumit Saroha

Keyword(s):

Neural Networks ◽

Fractional Order ◽

Finite Time ◽

Controller Design ◽

Fixed Time ◽

Uncertain Parameters ◽

Time Varying ◽

Bam Neural Networks ◽

Complex Valued

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Finite‐time and fixed‐time sliding mode control for discontinuous nonidentical recurrent neural networks with time‐varying delays

International Journal of Robust and Nonlinear Control ◽

10.1002/rnc.5875 ◽

2021 ◽

Author(s):

Chaouki Aouiti ◽

Mayssa Bessifi

Keyword(s):

Neural Networks ◽

Sliding Mode Control ◽

Recurrent Neural Networks ◽

Finite Time ◽

Sliding Mode ◽

Fixed Time ◽

Time Varying ◽

Mode Control

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Finite-time Synchronization of fractional-order complex-valued fuzzy cellular neural networks with time-varying delays

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-211183 ◽

2021 ◽

pp. 1-11

Author(s):

Wenbin Jin ◽

Wenxia Cui ◽

Zhenjie Wang

Keyword(s):

Neural Networks ◽

Fractional Order ◽

Finite Time ◽

Time Synchronization ◽

Sufficient Conditions ◽

Cellular Neural Networks ◽

Time Varying ◽

Order Complex ◽

Fuzzy Cellular Neural Networks ◽

Complex Valued

Finite-time synchronization is concerned for the fractional-order complex-valued fuzzy cellular neural networks (FOCVFCNNs) with leakage delay and time-varying delays. Without using the usual complex-valued system decomposition method, this paper designs the different forms of the controllers by using 2-norm. And we construct the appropriate Lyapunov functional and apply inequality analytical techniques, some new sufficient conditions are obtained to ensure finite-time synchronization of the FOCVFCNNs. The upper bound of setting-time function is obtained. Finally, numerical examples are examined to illustrate the effectiveness of the analytical results.

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