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Synchronization of Stochastic Memristive Neural Networks with Retarded and Advanced Argument

DOI: 10.4236/jilsa.2021.131001, PP. 1-14

Keywords: Synchronization, Memristive Neural Networks, Random Disturbance, Time-Delay Feedback, Adaptive Control, Retarded and Advanced System

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Abstract:

In this paper, we discuss the driving-response synchronization problem for two memristive neural networks with retarded and advanced arguments under the condition of additional noise. The control law is related to the linear time-delay feedback term, and the discontinuous feedback term. Moreover, the random different equation is used to prove the stability of this theory. At the end, the simulation results verify the correctness of the theoretical results.

References

[1]  Chua, L. (1971) Memristor—The Missing Circuit Element. IEEE Transactions on Circuit Theory, 18, 507-519.
https://doi.org/10.1109/TCT.1971.1083337
[2]  Mathur, N.D. (2008) The Fourth Circuit Element. Nature, 455, E13.
https://doi.org/10.1038/nature07437
[3]  Zhang, H.G., Wang, Z.S. and Liu, D.R. (2014) A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks. IEEE Transactions on Neural Networks and Learning Systems, 25, 1229-1262.
https://doi.org/10.1109/TNNLS.2014.2317880
[4]  Itoh, M. and Chua, L. (2014) Memristor Network. Springer, Berlin.
[5]  Pershin, Y.V. and Di Ventra, M. (2010) Experimental Demonstration of Associative Memory with Memristive Neural Networks. Neural Networks, 23, 881-886.
https://doi.org/10.1016/j.neunet.2010.05.001
[6]  Cao, J.D and Wang, J. (2003) Global Asymptotic Stability of a General Class of Recurrent Neural Networks with Time-Varying Delays. IEEE Transactions on Neural Networks, 50, 34-44.
https://doi.org/10.1109/TCSI.2002.807494
[7]  Cao, J.D. and Wang, J. (2005) Global Asymptotic and Robust Stability of Recurrent Neural Networks with Time Delays. IEEE Transactions on Circuits and Systems I: Regular Papers, 52, 417-426.
https://doi.org/10.1109/TCSI.2004.841574
[8]  Wang, Z.S. and Zhang, H.G. and Jiang, B. (2011) LMI-Based Approach for Global Asymptotic Stability Analysis of Recurrent Neural Networks with Various Delays and Structures. IEEE Transactions on Neural Networks, 22, 1032-1045.
https://doi.org/10.1109/TNN.2011.2131679
[9]  Wang, Z.S., Liu, L., Shan, Q.-H. and Zhang, H.G. (2015) Stability Criteria for Recurrent Neural Networks with Time-Varying Delay Based on Secondary Delay Partitioning Method. IEEE Transactions on Neural Networks and Learning Systems, 26, 2589-2595.
https://doi.org/10.1109/TNNLS.2014.2387434
[10]  Wang, Z.S., Ding, S.B., Huang, Z.J. and Zhang, H.G. (2015) Exponential Stability and Stabilization of Delayed Memristive Neural Networks Based on Quadratic Convex Combination Method. IEEE Transactions on Neural Networks and Learning Systems, 27, 2337-2350.
https://doi.org/10.1109/TNNLS.2015.2485259
[11]  Hu, J. and Wang, J. (2010) The 2010 International joint Conference on Neural Networks. Institute of Electrical and Electronics Engineers, 1-8.
[12]  Wu, A.L. and Zeng, Z.G. (2012) Dynamic Behaviors of Memristor-Based Recurrent Neural Networks with Time-Varying Delays. In: American Mathematical Society, Ed., Graduate Studies in Mathematics, Vol. 36, 1-10.
[13]  Cohen, M.A. and Grossberg, S. (1983) Absolute Stability of Global Pattern Formation and Parallel Memory Storage by Competitive Neural Networks. IEEE Transactions on Systems, Man, and Cybernetics, SMC-13, 815-826.
https://doi.org/10.1109/TSMC.1983.6313075
[14]  Duan, L., Huang, L.H. and Fang, X.W. (2017) Finite-Time Synchronization for Recurrent Neural Networks with Discontinuous Activations and Time-Varying Delays. Chaos, 27, Article ID: 013101.
https://doi.org/10.1063/1.4966177
[15]  Lu, W.L. and Chen, T.P. (2003) New Conditions on Global Stability of Cohen-Grossberg Neural Networks. Neural Computation, 15, 1173-1189.
https://doi.org/10.1162/089976603765202703
[16]  Rosenstein, M.T. and Collins, J.J. and De Luca, C.J. (1993) A Practical Method for Calculating Largest Lyapunov Exponents from Small Data Sets. Physica D: Nonlinear Phenomena, 65, 117-134.
https://doi.org/10.1016/0167-2789(93)90009-P
[17]  Xu, C.J. and Li, P.L. (2018) Periodic Dynamics for Memristor-Based Bidirectional Associative Memory Neural Networks with Leakage Delays and Time-Varying Delays. International Journal of Control, Automation and Systems, 16, 535-549.
https://doi.org/10.1007/s12555-017-0235-7
[18]  Tubiana, J. and Monasson, R. (2017) Emergence of Compositional Representations in Restricted Boltzmann Machines. Physical Review Letters, 118, Article ID: 138301.
https://doi.org/10.1103/PhysRevLett.118.138301
[19]  Tang, L.K., Lu, J-A., Lü, J.H. and Yu, X.H. (2012) Bifurcation Analysis of Synchronized Region in Complex Dynamical Networks. International Journal of Bifurcation and Chaos, 22, Article ID: 1250282.
https://doi.org/10.1142/S0218127412502823

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