Event-triggered impulsive synchronization of discrete-time coupled neural networks with stochastic perturbations and multiple delays

DOI10.1016/j.neunet.2020.09.012zbMath1478.93403OpenAlexW3088620893WikidataQ100501634 ScholiaQ100501634MaRDI QIDQ2057779

Leszek Rutkowski, Tingwen Huang, Xiaofan Li, Hui-yuan Li, Jian-an Fang

Publication date: 7 December 2021

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2020.09.012

zbMATH Keywords

synchronizationmultiple delaysevent-triggered impulsive controldiscrete-time coupled neural networks

Mathematics Subject Classification ID

Discrete-time control/observation systems (93C55) Discrete event control/observation systems (93C65) Stochastic systems in control theory (general) (93E03) Delay control/observation systems (93C43) Networked control (93B70) Impulsive control/observation systems (93C27)

Related Items (9)

Non-fragile control design for stochastic Markov jump system with multiple delays and cyber attacks ⋮ Stability and finite/fixed-time attractivity of time-delayed Filippov system: application to switched neural networks ⋮ Event-triggered \textit{delayed} impulsive control for nonlinear systems with application to complex neural networks ⋮ Periodicity and multi-periodicity generated by impulses control in delayed Cohen-Grossberg-type neural networks with discontinuous activations ⋮ General decay anti-synchronization and \(H_\infty\) anti-synchronization of coupled reaction-diffusion complex-valued memristive neural networks ⋮ Lag \(H_\infty\) synchronization of coupled neural networks with multiple state couplings and multiple delayed state couplings ⋮ Multi-periodicity of switched neural networks with time delays and periodic external inputs under stochastic disturbances ⋮ Event-triggered impulsive cluster synchronization of coupled reaction-diffusion neural networks and its application to image encryption ⋮ Passivity analysis of coupled stochastic neural networks with multiweights

Cites Work

• Impulsive synchronization of discrete-time networked oscillators with partial input saturation
• Robust control of a class of uncertain nonlinear systems
• A new contribution for the impulsive synchronization of fractional-order discrete-time chaotic systems
• Stabilization of discrete-time dynamical systems under event-triggered impulsive control with and without time-delays
• Exponential stability of discrete time uncertain systems with time-varying delay
• Synchronization of memristive neural networks with mixed delays via quantized intermittent control
• Composite synchronization control for delayed coupling complex dynamical networks via a disturbance observer-based method
• Input-to-state stability for nonlinear systems with stochastic impulses
• Impulsive synchronization of stochastic reaction-diffusion neural networks with mixed time delays
• Finite-time synchronization of stochastic coupled neural networks subject to Markovian switching and input saturation
• Event-triggered impulsive control on quasi-synchronization of memristive neural networks with time-varying delays
• New stability results for Takagi-Sugeno fuzzy Cohen-Grossberg neural networks with multiple delays
• Synchronization of impulsive coupled complex-valued neural networks with delay: the matrix measure method
• Synchronization of chaotic neural networks with time delay via \textit{distributed delayed impulsive control}
• Synchronization regions of discrete-time dynamical networks with impulsive couplings
• Synchronization of discrete-time neural networks with delays and Markov jump topologies based on tracker information
• Master-slave exponential synchronization of delayed complex-valued memristor-based neural networks via impulsive control
• Optimal impulsive control in periodic ecosystem
• Linear Matrix Inequalities in System and Control Theory
• Event‐triggered control via impulses for exponential stabilization of discrete‐time delayed systems and networks
• Event-Triggered Control for Consensus Problem in Multi-Agent Systems With Quantized Relative State Measurements and External Disturbance
• The relative performance of ensemble methods with deep convolutional neural networks for image classification

This page was built for publication: Event-triggered impulsive synchronization of discrete-time coupled neural networks with stochastic perturbations and multiple delays