Aperiodic intermittent pinning control for exponential synchronization of memristive neural networks with time-varying delays

Abstract This paper is concerned with the problem of pinning synchronization for memristive neural networks with time-varying delays via aperiodic intermittent control. By applying aperiodic intermittent control to partial nodes of the memristive neural networks, some new general criteria for global exponential synchronization are derived based on the theory of nonsmooth analysis. The obtained results indicate that it is the control rates rather than the control periods or control widths are involved in the synchronization criteria. In addition, a feasible region of the control gains and control rates is established for achieving global exponential synchronization. Finally, numerical simulations are given to verify the correctness of our theoretical analysis.

[1]  Zhigang Zeng,et al.  New results on global exponential dissipativity analysis of memristive inertial neural networks with distributed time-varying delays , 2018, Neural Networks.

[2]  Zhigang Zeng,et al.  Exponential Stabilization of Memristive Neural Networks With Time Delays , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[3]  Guodong Zhang,et al.  Global exponential stability of a class of memristor-based recurrent neural networks with time-varying delays , 2012, Neurocomputing.

[4]  Shuiming Cai,et al.  Outer synchronization between two hybrid-coupled delayed dynamical networks via aperiodically adaptive intermittent pinning control , 2016, Complex..

[5]  A. Thomas,et al.  Memristor-based neural networks , 2013 .

[6]  Guanrong Chen,et al.  Synchronization of delayed chaotic systems with parameter mismatches by using intermittent linear state feedback , 2009 .

[7]  Shengqin Jiang,et al.  Adaptive outer synchronization between two complex delayed dynamical networks via aperiodically intermittent pinning control , 2017, Neurocomputing.

[8]  Jun Wang,et al.  Global uniform asymptotic stability of memristor-based recurrent neural networks with time delays , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[9]  Peng Shi,et al.  Fuzzy Adaptive Control Design and Discretization for a Class of Nonlinear Uncertain Systems , 2016, IEEE Transactions on Cybernetics.

[10]  Lihong Huang,et al.  New conditions on synchronization of memristor-based neural networks via differential inclusions , 2016, Neurocomputing.

[11]  Wei Yang Lu,et al.  Nanoscale memristor device as synapse in neuromorphic systems. , 2010, Nano letters.

[12]  Quan Yin,et al.  Adaptive Synchronization of Memristor-Based Neural Networks with Time-Varying Delays , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[13]  Zhidong Teng,et al.  Exponential stabilization and synchronization of neural networks with time-varying delays via periodically intermittent control , 2010 .

[14]  Zhigang Zeng,et al.  Dynamic behaviors of memristor-based recurrent neural networks with time-varying delays , 2012, Neural Networks.

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

[16]  Qiankun Song,et al.  Stabilization and synchronization of chaotic systems with mixed time-varying delays via intermittent control with non-fixed both control period and control width , 2015, Neurocomputing.

[17]  Tianping Chen,et al.  Synchronization of Linearly Coupled Networks With Delays via Aperiodically Intermittent Pinning Control , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[18]  Yongqing Yang,et al.  Lag synchronization for fractional-order memristive neural networks via period intermittent control , 2017, Nonlinear Dynamics.

[19]  Hongmin Li,et al.  Fuzzy-Approximation-Based Adaptive Output-Feedback Control for Uncertain Nonsmooth Nonlinear Systems , 2018, IEEE Transactions on Fuzzy Systems.

[20]  Shuiming Cai,et al.  Pinning synchronization of complex directed dynamical networks under decentralized adaptive strategy for aperiodically intermittent control , 2017, Nonlinear Dynamics.

[21]  Zhigang Zeng,et al.  Global stabilization analysis of inertial memristive recurrent neural networks with discrete and distributed delays , 2018, Neural Networks.

[22]  Shuiming Cai,et al.  Exponential synchronization of chaotic systems with time-varying delays and parameter mismatches via intermittent control. , 2011, Chaos.

[23]  Jinde Cao,et al.  A New Framework for Analysis on Stability and Bifurcation in a Class of Neural Networks With Discrete and Distributed Delays , 2015, IEEE Transactions on Cybernetics.

[24]  Xiwei Liu,et al.  Cluster Synchronization in Directed Networks Via Intermittent Pinning Control , 2011, IEEE Transactions on Neural Networks.

[25]  Haijun Jiang,et al.  Delay-dependent dynamical analysis of complex-valued memristive neural networks: Continuous-time and discrete-time cases , 2018, Neural Networks.

[26]  Zhigang Zeng,et al.  Synchronization control of a class of memristor-based recurrent neural networks , 2012, Inf. Sci..

[27]  Massimiliano Di Ventra,et al.  Experimental demonstration of associative memory with memristive neural networks , 2009, Neural Networks.

[28]  Jinde Cao,et al.  Exponential synchronization of memristive Cohen–Grossberg neural networks with mixed delays , 2014, Cognitive Neurodynamics.

[29]  Guodong Zhang,et al.  New results on synchronization control of delayed memristive neural networks , 2015 .

[30]  Derong Liu,et al.  Pinning synchronization of memristor-based neural networks with time-varying delays , 2017, Neural Networks.

[31]  Xin Wang,et al.  Dual-stage impulsive control for synchronization of memristive chaotic neural networks with discrete and continuously distributed delays , 2015, Neurocomputing.

[32]  Wei Zhang,et al.  Stability and synchronization of memristor-based coupling neural networks with time-varying delays via intermittent control , 2016, Neurocomputing.

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

[34]  Jinde Cao,et al.  New synchronization criteria for memristor-based networks: Adaptive control and feedback control schemes , 2015, Neural Networks.

[35]  Guodong Zhang,et al.  Exponential Stabilization of Memristor-based Chaotic Neural Networks with Time-Varying Delays via Intermittent Control , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[36]  J Joshua Yang,et al.  Memristive devices for computing. , 2013, Nature nanotechnology.

[37]  D. Stewart,et al.  The missing memristor found , 2008, Nature.

[38]  Ju H. Park,et al.  Quantized Static Output Feedback Control For Discrete-Time Systems , 2018, IEEE Transactions on Industrial Informatics.

[39]  Zhigang Zeng,et al.  Global exponential synchronization of memristor-based recurrent neural networks with time-varying delays , 2013, Neural Networks.

[40]  Fei Wang,et al.  Synchronization analysis of fractional-order neural networks with time-varying delays via discontinuous neuron activations , 2018, Neurocomputing.

[41]  Tingwen Huang,et al.  Global Exponential Synchronization of Memristive Competitive Neural Networks with Time-Varying Delay via Nonlinear Control , 2018, Neural Processing Letters.

[42]  Guodong Zhang,et al.  Exponential synchronization of delayed memristor-based chaotic neural networks via periodically intermittent control , 2014, Neural Networks.

[43]  Jinde Cao,et al.  Pth Moment Exponential Stochastic Synchronization of Coupled Memristor-based Neural Networks with Mixed Delays via Delayed Impulsive Control , 2015, Neural Networks.

[44]  Jigui Jian,et al.  Finite-time synchronization of inertial memristive neural networks with time-varying delays via sampled-date control , 2017, Neurocomputing.

[45]  Wenwu Yu,et al.  Synchronization via Pinning Control on General Complex Networks , 2013, SIAM J. Control. Optim..

[46]  Zengrong Liu,et al.  Pinning synchronization of hybrid-coupled directed delayed dynamical network via intermittent control. , 2014, Chaos.

[47]  Guang-Hong Yang,et al.  New Results on Output Feedback $H_{\infty} $ Control for Linear Discrete-Time Systems , 2014, IEEE Transactions on Automatic Control.