Asynchronous dissipative stabilization for stochastic Markov-switching neural networks with completely- and incompletely-known transition rates

[1]  Jianping Zhou,et al.  Input-to-state Stabilization of Delayed Semi-Markovian Jump Neural Networks Via Sampled-Data Control , 2022, Neural Processing Letters.

[2]  R. Manivannan,et al.  Unified dissipativity state estimation for delayed generalized impulsive neural networks with leakage delay effects , 2022, Knowl. Based Syst..

[3]  Jianping Zhou,et al.  Energy-to-peak synchronization for uncertain reaction-diffusion delayed neural networks , 2022, Physica Scripta.

[4]  Y. Niu,et al.  Asynchronous Boundary Control of Markov Jump Neural Networks With Diffusion Terms , 2022, IEEE Transactions on Cybernetics.

[5]  Wei Sun,et al.  Asynchronous H∞ Dynamic Output Feedback Control for Markovian Jump Neural Networks with Time-varying Delays , 2022, International Journal of Control, Automation and Systems.

[6]  R. Rakkiyappan,et al.  Hidden Markov-Model-Based Control Design for Multilateral Teleoperation System With Asymmetric Time-Varying Delays , 2022, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[7]  Baozhu Du,et al.  Investigation on Stability of Positive Singular Markovian Jump Systems With Mode-Dependent Derivative-Term Coefficient , 2022, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[8]  Peng Cheng,et al.  Asynchronous Output Feedback Control for a Class of Conic-Type Nonlinear Hidden Markov Jump Systems Within a Finite-Time Interval , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[9]  Hui Peng,et al.  H ∞ asynchronous synchronisation control for Markovian coupled delayed neural networks with missing information , 2021, Int. J. Syst. Sci..

[10]  Xia Huang,et al.  Stochastic Sampled-Data Exponential Synchronization of Markovian Jump Neural Networks With Time-Varying Delays , 2021, IEEE Transactions on Neural Networks and Learning Systems.

[11]  Wassim M. Haddad,et al.  Dissipativity Theory for Discrete-Time Nonlinear Stochastic Dynamical Systems, Part I: Input-Output and State Properties , 2021, 2021 American Control Conference (ACC).

[12]  Housheng Su,et al.  Finite-Time Synchronization of Markovian Coupled Neural Networks With Delays via Intermittent Quantized Control: Linear Programming Approach , 2021, IEEE Transactions on Neural Networks and Learning Systems.

[13]  Jianlong Qiu,et al.  Synchronization criteria of delayed inertial neural networks with generally Markovian jumping , 2021, Neural Networks.

[14]  Y. Joo,et al.  Resilient Reliable Hθ Load Frequency Control of Power System With Random Gain Fluctuations , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[15]  Yong Xu,et al.  Resilient Asynchronous State Estimation for Markovian Jump Neural Networks Subject to Stochastic Nonlinearities and Sensor Saturations , 2021, IEEE Transactions on Cybernetics.

[16]  José Jesús De Rubio Stability Analysis of the Modified Levenberg-Marquardt Algorithm for the Artificial Neural Network Training. , 2020, IEEE transactions on neural networks and learning systems.

[17]  Yonggang Chen,et al.  L2-L∞ filtering for stochastic delayed systems with randomly occurring nonlinearities and sensor saturation , 2020, Int. J. Syst. Sci..

[18]  Jinde Cao,et al.  Asynchronous dissipative filtering for nonhomogeneous Markov switching neural networks with variable packet dropouts , 2020, Neural Networks.

[19]  Peter E. Latham,et al.  Noisy Synaptic Conductance: Bug or a Feature? , 2020, Trends in Neurosciences.

[20]  Shiming Chen,et al.  Extended dissipativity asynchronous static output feedback control of Markov jump systems , 2020, Inf. Sci..

[21]  Ahmed Alsaedi,et al.  Extended dissipativity and event-triggered synchronization for T–S fuzzy Markovian jumping delayed stochastic neural networks with leakage delays via fault-tolerant control , 2020, Soft Comput..

[22]  Jianwei Xia,et al.  Resilient fault-tolerant anti-synchronization for stochastic delayed reaction-diffusion neural networks with semi-Markov jump parameters , 2020, Neural Networks.

[23]  Junwei Lu,et al.  Integral sliding mode synchronization control for Markovian jump inertial memristive neural networks with reaction-diffusion terms , 2020, Neurocomputing.

[24]  C. Bergmeir,et al.  Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions , 2019, International Journal of Forecasting.

[25]  M. Syed Ali,et al.  Decentralised event-triggered impulsive synchronisation for semi-Markovian jump delayed neural networks with leakage delay and randomly occurring uncertainties , 2019, Int. J. Syst. Sci..

[26]  Fernando Gama,et al.  Stability Properties of Graph Neural Networks , 2019, IEEE Transactions on Signal Processing.

[27]  Gopala Krishna Anumanchipalli,et al.  Speech synthesis from neural decoding of spoken sentences , 2018, bioRxiv.

[28]  Jinde Cao,et al.  An Arcak-type state estimation design for time-delayed static neural networks with leakage term based on unified criteria , 2018, Neural Networks.

[29]  Funa Zhou,et al.  Event‐triggered dissipative synchronization for Markovian jump neural networks with general transition probabilities , 2018 .

[30]  Rathinasamy Sakthivel,et al.  Finite-time synchronization of stochastic coupled neural networks subject to Markovian switching and input saturation , 2018, Neural Networks.

[31]  Fuwen Yang,et al.  Event-Triggered Asynchronous Guaranteed Cost Control for Markov Jump Discrete-Time Neural Networks With Distributed Delay and Channel Fading , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[32]  Z. Xiang,et al.  Passivity Analysis of Stochastic Memristor-Based Complex-Valued Recurrent Neural Networks with Mixed Time-Varying Delays , 2018, Neural Processing Letters.

[33]  Ju H. Park,et al.  An Asynchronous Operation Approach to Event-Triggered Control for Fuzzy Markovian Jump Systems With General Switching Policies , 2018, IEEE Transactions on Fuzzy Systems.

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

[35]  Qian Ma,et al.  Non-fragile observer-based H∞ control for stochastic time-delay systems , 2016, Appl. Math. Comput..

[36]  Dan Ye,et al.  A Separated Approach to Control of Markov Jump Nonlinear Systems With General Transition Probabilities , 2016, IEEE Transactions on Cybernetics.

[37]  Shengyuan Xu,et al.  Filtering of Markovian Jump Delay Systems Based on a New Performance Index , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[38]  Shengyuan Xu,et al.  Delay-Dependent $H_{\infty }$ Control and Filtering for Uncertain Markovian Jump Systems With Time-Varying Delays , 2007, IEEE Transactions on Circuits and Systems I: Regular Papers.

[39]  P. Khargonekar,et al.  Robust stabilization of linear systems with norm-bounded time-varying uncertainty , 1988 .

[40]  X. Mao Stability of stochastic differential equations with Markovian switching , 1999 .