Finite/fixed-time synchronization of delayed memristive reaction-diffusion neural networks

Abstract This paper is concerned with the finite/fixed-time synchronization (FFTS) problems of two delayed memristive reaction–diffusion neural networks (MRDNNs). By designing appropriate state feedback controllers, utilizing the Lyapunov function method and inequality techniques, several sufficient criteria are derived to guarantee the FFTS of the drive-response MRDNNs. Taking into account both the influences of time and space, the model, described as a state-dependent switching system here, is more complex and closer to practical applications than those in the existing results. Finally, an example is presented to substantiate the effectiveness of the theoretical results.

[1]  Zhigang Zeng,et al.  Synchronization of Reaction–Diffusion Neural Networks With Dirichlet Boundary Conditions and Infinite Delays , 2017, IEEE Transactions on Cybernetics.

[2]  Qingling Zhang,et al.  Finite-time synchronization for second-order nonlinear multi-agent system via pinning exponent sliding mode control. , 2016, ISA transactions.

[3]  Dennis S. Bernstein,et al.  Finite-Time Stability of Continuous Autonomous Systems , 2000, SIAM J. Control. Optim..

[4]  Byeong Seok Ahn,et al.  The integrated methodology of rough set theory and artificial neural network for business failure prediction , 2000 .

[5]  Zhidong Teng,et al.  Finite-time synchronization for fuzzy cellular neural networks with time-varying delays , 2016, Fuzzy Sets Syst..

[6]  Jinde Cao,et al.  Fixed-time synchronization of quaternion-valued memristive neural networks with time delays , 2019, Neural Networks.

[7]  Tingwen Huang,et al.  Finite-time synchronization of inertial memristive neural networks with time delay via delay-dependent control , 2018, Neurocomputing.

[8]  Jun Zhou,et al.  Asymptotical synchronization for delayed stochastic neural networks with uncertainty via adaptive control , 2016 .

[9]  Qing-Long Han,et al.  Fixed-time synchronization for coupled delayed neural networks with discontinuous or continuous activations , 2018, Neurocomputing.

[10]  Xiaoyang Liu,et al.  A Switching Approach to Designing Finite-Time Synchronization Controllers of Coupled Neural Networks , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[11]  Tingwen Huang,et al.  Fixed-time stability of dynamical systems and fixed-time synchronization of coupled discontinuous neural networks , 2017, Neural Networks.

[12]  Haijun Jiang,et al.  Finite-time and fixed-time synchronization of discontinuous complex networks: A unified control framework design , 2018, J. Frankl. Inst..

[13]  Zhidong Teng,et al.  Impulsive Control and Synchronization for Delayed Neural Networks With Reaction–Diffusion Terms , 2010, IEEE Transactions on Neural Networks.

[14]  Wu Jigang,et al.  Pinning Control for Synchronization of Coupled Reaction-Diffusion Neural Networks With Directed Topologies , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[15]  Zhanshan Wang,et al.  Exponential Stabilization of Memristive Neural Networks via Saturating Sampled-Data Control , 2017, IEEE Transactions on Cybernetics.

[16]  Chee Peng Lim,et al.  Asymptotical synchronization of Lur'e systems using network reliable control , 2017 .

[17]  Zhigang Zeng,et al.  Impulsive synchronization of stochastic reaction-diffusion neural networks with mixed time delays , 2018, Neural Networks.

[18]  Kuolin Hsu,et al.  Artificial Neural Network Modeling of the Rainfall‐Runoff Process , 1995 .

[19]  Feiqi Deng,et al.  Synchronization of Reaction–Diffusion Stochastic Complex Networks , 2019 .

[20]  Jun Wang,et al.  A systematic method for analyzing robust stability of interval neural networks with time-delays based on stability criteria , 2014, Neural Networks.

[21]  Zhigang Zeng,et al.  Synchronization of Coupled Reaction–Diffusion Neural Networks With Directed Topology via an Adaptive Approach , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[22]  Kexue Zhang,et al.  Pinning Impulsive Synchronization of Reaction–Diffusion Neural Networks With Time-Varying Delays , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[23]  Shengyuan Xu,et al.  Delay-Dependent Stability Criteria for Reaction–Diffusion Neural Networks With Time-Varying Delays , 2013, IEEE Transactions on Cybernetics.

[24]  Huijun Gao,et al.  Distributed Robust Synchronization of Dynamical Networks With Stochastic Coupling , 2014, IEEE Transactions on Circuits and Systems I: Regular Papers.

[25]  Hui Zhao,et al.  Finite-time synchronization for multi-link complex networks via discontinuous control , 2017 .

[26]  Jinde Cao,et al.  Finite-time and fixed-time synchronization analysis of inertial memristive neural networks with time-varying delays , 2017, Cognitive Neurodynamics.

[27]  Jinde Cao,et al.  Robust fixed-time synchronization for uncertain complex-valued neural networks with discontinuous activation functions , 2017, Neural Networks.

[28]  Dianguo Xu,et al.  Synchronization of delayed coupled reaction‐diffusion systems on networks , 2015 .

[29]  Junguo Lu Global exponential stability and periodicity of reaction–diffusion delayed recurrent neural networks with Dirichlet boundary conditions , 2008 .

[30]  X. Xia,et al.  Semi-global finite-time observers for nonlinear systems , 2008, Autom..

[31]  Yu Tang,et al.  Terminal sliding mode control for rigid robots , 1998, Autom..

[32]  Tingwen Huang,et al.  Global exponential synchronization of multiple coupled inertial memristive neural networks with time-varying delay via nonlinear coupling , 2018, Neural Networks.

[33]  Andrey Polyakov,et al.  Nonlinear Feedback Design for Fixed-Time Stabilization of Linear Control Systems , 2012, IEEE Transactions on Automatic Control.

[34]  Robert J. Marks,et al.  Electric load forecasting using an artificial neural network , 1991 .

[35]  Jun Wang,et al.  Passivity and Passification of Memristor-Based Recurrent Neural Networks With Time-Varying Delays , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[36]  Zhenyuan Guo,et al.  Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control , 2016, Neural Networks.

[37]  M. Forti,et al.  Generalized Lyapunov approach for convergence of neural networks with discontinuous or non-Lipschitz activations , 2006 .

[38]  Jun Wang,et al.  Robust Synchronization of Multiple Memristive Neural Networks With Uncertain Parameters via Nonlinear Coupling , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[39]  Adel M. Alimi,et al.  Finite-time and fixed-time synchronization of a class of inertial neural networks with multi-proportional delays and its application to secure communication , 2019, Neurocomputing.

[40]  Jinde Cao,et al.  Robust fixed-time synchronization of delayed Cohen-Grossberg neural networks , 2016, Neural Networks.

[41]  Daniel W. C. Ho,et al.  Globally Exponential Synchronization and Synchronizability for General Dynamical Networks , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[42]  Jun Wang,et al.  Attractivity Analysis of Memristor-Based Cellular Neural Networks With Time-Varying Delays , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[43]  Tingwen Huang,et al.  Global exponential synchronization of inertial memristive neural networks with time-varying delay via nonlinear controller , 2018, Neural Networks.

[44]  Yanke Du,et al.  Robust synchronization of an array of neural networks with hybrid coupling and mixed time delays. , 2014, ISA transactions.

[45]  L. Chua Memristor-The missing circuit element , 1971 .

[46]  Jinde Cao,et al.  Robust synchronization of coupled neural networks with mixed delays and uncertain parameters by intermittent pinning control , 2014, Neurocomputing.

[47]  Jian-ping Cai,et al.  Asymptotical synchronization control of discrete-time neural networks with time-varying delays and controller nonlinearity , 2017, 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC).

[48]  Zhigang Zeng,et al.  Lagrange Stability of Memristive Neural Networks With Discrete and Distributed Delays , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[49]  J. Tour,et al.  Electronics: The fourth element , 2008, Nature.

[50]  Leon O. Chua Resistance switching memories are memristors , 2011 .