Global exponential synchronization of delayed memristive neural networks with reaction-diffusion terms

This paper investigates the global exponential synchronization problem of delayed memristive neural networks (MNNs) with reaction-diffusion terms. First, by utilizing the pinning control technique, two novel kinds of control methods are introduced to achieve synchronization of delayed MNNs with reaction-diffusion terms. Then, with the help of inequality techniques, pinning control technique, the drive-response concept and Lyapunov functional method, two sufficient conditions are obtained in the form of algebraic inequalities, which can be used for ensuring the exponential synchronization of the proposed delayed MNNs with reaction-diffusion terms. Moreover, the obtained results based on algebraic inequality complement and improve the previously known results. Finally, two illustrative examples are given to support the effectiveness and validity of the obtained theoretical results.

[1]  Zhigang Zeng,et al.  A Flux-Controlled Logarithmic Memristor Model and Emulator , 2018, Circuits Syst. Signal Process..

[2]  Shouming Zhong,et al.  Function projective synchronization of complex networks with asymmetric coupling via adaptive and pinning feedback control. , 2016, ISA transactions.

[3]  Zhigang Zeng,et al.  Passivity analysis of coupled neural networks with reaction-diffusion terms and mixed delays , 2018, J. Frankl. Inst..

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

[5]  Huaguang Zhang,et al.  Dissipativity Analysis for Stochastic Memristive Neural Networks With Time-Varying Delays: A Discrete-Time Case , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[6]  Hamid Reza Karimi,et al.  Improved Stability and Stabilization Results for Stochastic Synchronization of Continuous-Time Semi-Markovian Jump Neural Networks With Time-Varying Delay , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[7]  M. Syed Ali,et al.  Decentralized event-triggered synchronization of uncertain Markovian jumping neutral-type neural networks with mixed delays , 2017, Neural Networks.

[8]  Derong Liu,et al.  Robust synchronization of memristive neural networks with strong mismatch characteristics via pinning control , 2018, Neurocomputing.

[9]  Shiping Wen,et al.  Quantized synchronization of memristive neural networks with time-varying delays via super-twisting algorithm , 2020, Neurocomputing.

[10]  Tingwen Huang,et al.  Finite-Time Passivity and Synchronization of Coupled Reaction–Diffusion Neural Networks With Multiple Weights , 2019, IEEE Transactions on Cybernetics.

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

[12]  Fuad E. Alsaadi,et al.  Stability analysis for discrete-time stochastic memristive neural networks with both leakage and probabilistic delays , 2018, Neural Networks.

[13]  Zhigang Zeng,et al.  Passivity analysis of delayed reaction-diffusion memristor-based neural networks , 2019, Neural Networks.

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

[15]  Lihong Huang,et al.  Finite-Time Stabilization of Delayed Memristive Neural Networks: Discontinuous State-Feedback and Adaptive Control Approach , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[16]  Shiping Wen,et al.  Sliding mode control of neural networks via continuous or periodic sampling event-triggering algorithm , 2020, Neural Networks.

[17]  Jinde Cao,et al.  Exponential Synchronization of Memristive Neural Networks With Delays: Interval Matrix Method , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[18]  Jinde Cao,et al.  Synchronization criteria for multiple memristor-based neural networks with time delay and inertial term , 2018 .

[19]  Zhigang Zeng,et al.  General memristor with applications in multilayer neural networks , 2018, Neural Networks.

[20]  Weiwei Liu,et al.  Multi-Label Image Classification by Feature Attention Network , 2019, IEEE Access.

[21]  Jinde Cao,et al.  Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays , 2018, J. Artif. Intell. Soft Comput. Res..

[22]  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.

[23]  Shiping Wen,et al.  Passivity and passification of memristive recurrent neural networks with multi-proportional delays and impulse , 2020, Appl. Math. Comput..

[24]  Lihong Huang,et al.  Generalized pinning synchronization of delayed Cohen-Grossberg neural networks with discontinuous activations , 2018, Neural Networks.

[25]  Jinde Cao,et al.  Passivity analysis of memristive neural networks with probabilistic time-varying delays , 2016, Neurocomputing.

[26]  Zhigang Zeng,et al.  Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[27]  Pagavathigounder Balasubramaniam,et al.  Synchronization of Markovian jumping inertial neural networks and its applications in image encryption , 2016, Neural Networks.

[28]  Zhigang Zeng,et al.  Adjusting Learning Rate of Memristor-Based Multilayer Neural Networks via Fuzzy Method , 2019, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[29]  Yi Zhao,et al.  Quasi-Synchronization of Coupled Nonlinear Memristive Neural Networks With Time Delays by Pinning Control , 2018, IEEE Access.

[30]  Zhigang Zeng,et al.  GST-memristor-based online learning neural networks , 2018, Neurocomputing.

[31]  Zhigang Zeng,et al.  Fuzzy Control for Uncertain Vehicle Active Suspension Systems via Dynamic Sliding-Mode Approach , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[32]  Rong Yao,et al.  Adaptive anti-synchronization and H∞ anti-synchronization for memristive neural networks with mixed time delays and reaction-diffusion terms , 2015, Neurocomputing.

[33]  Shiping Wen,et al.  Synchronization of memristive neural networks with leakage delay and parameters mismatch via event-triggered control , 2019, Neural Networks.

[34]  Zhigang Zeng,et al.  Design of memristor-based image convolution calculation in convolutional neural network , 2016, Neural Computing and Applications.

[35]  Jinde Cao,et al.  Pinning-controlled synchronization of delayed neural networks with distributed-delay coupling via impulsive control , 2017, Neural Networks.

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

[37]  Zhigang Zeng,et al.  Sparse fully convolutional network for face labeling , 2019, Neurocomputing.

[38]  Huaguang Zhang,et al.  Quasi-Synchronization of Delayed Memristive Neural Networks via Region-Partitioning-Dependent Intermittent Control , 2019, IEEE Transactions on Cybernetics.

[39]  Ruoxia Li,et al.  Synchronization of delayed Markovian jump memristive neural networks with reaction–diffusion terms via sampled data control , 2016, Int. J. Mach. Learn. Cybern..

[40]  Zhigang Zeng,et al.  Synchronization of Nonidentical Neural Networks With Unknown Parameters and Diffusion Effects via Robust Adaptive Control Techniques , 2019, IEEE Transactions on Cybernetics.

[41]  Wei Zhang,et al.  Adaptive synchronization of memristive neural networks with time-varying delays and reaction-diffusion term , 2017, Appl. Math. Comput..

[42]  R. Rakkiyappan,et al.  Sampled-data synchronization of randomly coupled reaction–diffusion neural networks with Markovian jumping and mixed delays using multiple integral approach , 2017, Neural Computing and Applications.

[43]  Young Hoon Joo,et al.  Adaptive Synchronization of Reaction–Diffusion Neural Networks and Its Application to Secure Communication , 2020, IEEE Transactions on Cybernetics.

[44]  Huijun Gao,et al.  A Constrained Evolutionary Computation Method for Detecting Controlling Regions of Cortical Networks , 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[45]  Qintao Gan,et al.  Adaptive synchronization of stochastic neural networks with mixed time delays and reaction–diffusion terms , 2012 .

[46]  Zhigang Zeng,et al.  Memristor-based circuit implementation of pulse-coupled neural network with dynamical threshold generators , 2018, Neurocomputing.

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

[48]  Jinde Cao,et al.  Lag Synchronization of Memristor-Based Coupled Neural Networks via $\omega $ -Measure , 2016, IEEE Transactions on Neural Networks and Learning Systems.

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

[50]  Zhigang Zeng,et al.  CLU-CNNs: Object detection for medical images , 2019, Neurocomputing.

[51]  Victor Sreeram,et al.  Controlling Chaos in a Memristor Based Circuit Using a Twin-T Notch Filter , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[52]  Wenwu Yu,et al.  On pinning synchronization of complex dynamical networks , 2009, Autom..

[53]  Fuad E. Alsaadi,et al.  Global exponential stability and lag synchronization for delayed memristive fuzzy Cohen-Grossberg BAM neural networks with impulses , 2018, Neural Networks.

[54]  Jinde Cao,et al.  Bipartite synchronization in coupled delayed neural networks under pinning control , 2018, Neural Networks.

[55]  Jinde Cao,et al.  Synchronization of hybrid-coupled heterogeneous networks: Pinning control and impulsive control schemes , 2014, J. Frankl. Inst..

[56]  Yong Xu,et al.  Remote Estimator Design for Time-Delay Neural Networks Using Communication State Information , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[57]  Yang Tang,et al.  Stability Analysis of Stochastic Delayed Systems With an Application to Multi-Agent Systems , 2016, IEEE Transactions on Automatic Control.

[58]  Jinde Cao,et al.  Stability analysis of reaction-diffusion uncertain memristive neural networks with time-varying delays and leakage term , 2016, Appl. Math. Comput..

[59]  Weiwei Liu,et al.  Generating Realistic Videos From Keyframes With Concatenated GANs , 2019, IEEE Transactions on Circuits and Systems for Video Technology.

[60]  Zhigang Zeng,et al.  Aperiodic Sampled-Data Sliding-Mode Control of Fuzzy Systems With Communication Delays Via the Event-Triggered Method , 2016, IEEE Transactions on Fuzzy Systems.

[61]  G. Subramanyam,et al.  A Memristor Device Model , 2011, IEEE Electron Device Letters.

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

[63]  Dong Yue,et al.  Relaxed Real-Time Scheduling Stabilization of Discrete-Time Takagi–Sugeno Fuzzy Systems via An Alterable-Weights-Based Ranking Switching Mechanism , 2018, IEEE Transactions on Fuzzy Systems.

[64]  Qing-Long Han,et al.  Fixed-time pinning-controlled synchronization for coupled delayed neural networks with discontinuous activations , 2019, Neural Networks.

[65]  Zhigang Zeng,et al.  Memristive LSTM Network for Sentiment Analysis , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[66]  Jinde Cao,et al.  Synchronization of discrete-time neural networks with delays and Markov jump topologies based on tracker information , 2017, Neural Networks.

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

[68]  Jinde Cao,et al.  H∞ state estimation of stochastic memristor-based neural networks with time-varying delays , 2018, Neural Networks.

[69]  Yiran Chen,et al.  Memristor-Based Design of Sparse Compact Convolutional Neural Network , 2020, IEEE Transactions on Network Science and Engineering.

[70]  Yin Yang,et al.  Memristor-Based Echo State Network With Online Least Mean Square , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[71]  Frank L. Lewis,et al.  Synchronization for an array of neural networks with hybrid coupling by a novel pinning control strategy , 2016, Neural Networks.

[72]  Zhigang Zeng,et al.  New results on anti-synchronization of switched neural networks with time-varying delays and lag signals , 2016, Neural Networks.

[73]  Chee Peng Lim,et al.  Synchronization of an Inertial Neural Network With Time-Varying Delays and Its Application to Secure Communication , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[74]  Shiping Wen,et al.  Passivity and passification of memristive neural networks with leakage term and time-varying delays , 2019, Appl. Math. Comput..

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

[76]  Chuandong Li,et al.  Exponential Lag Synchronization of Memristive Neural Networks with Reaction Diffusion Terms via Neural Activation Function Control and Fuzzy Model , 2018, Asian Journal of Control.