Event-triggered state estimation for discrete-time multidelayed neural networks with stochastic parameters and incomplete measurements
In this paper, the event-triggered state estimation problem is investigated for a class of
discrete-time multidelayed neural networks with stochastic parameters and incomplete …
discrete-time multidelayed neural networks with stochastic parameters and incomplete …
Fractional order fixed-time nonsingular terminal sliding mode synchronization and control of fractional order chaotic systems
J Ni, L Liu, C Liu, X Hu - Nonlinear dynamics, 2017 - Springer
This paper presents fractional order fixed-time nonsingular terminal sliding mode control for
stabilization and synchronization of fractional order chaotic systems with uncertainties and …
stabilization and synchronization of fractional order chaotic systems with uncertainties and …
Exponential synchronization of neural networks with time-varying delays via dynamic intermittent output feedback control
This paper addresses the exponential synchronization problem for neural networks with time-
varying delays. First, a novel controller is presented by combining intermittent control with …
varying delays. First, a novel controller is presented by combining intermittent control with …
Finite-time synchronization control for uncertain Markov jump neural networks with input constraints
This paper is concerned with the problem of finite-time synchronization control for uncertain
Markov jump neural networks in the presence of constraints on the control input amplitude …
Markov jump neural networks in the presence of constraints on the control input amplitude …
Pinning sampled-data synchronization of coupled inertial neural networks with reaction-diffusion terms and time-varying delays
The intention of this paper is to explore the problem of pinning sampled-data
synchronization of coupled reaction-diffusion neural networks with added inertia and time …
synchronization of coupled reaction-diffusion neural networks with added inertia and time …
Event-triggered H∞ state estimation for discrete-time delayed switched stochastic neural networks with persistent dwell-time switching regularities and sensor …
J Suo, N Li, Q Li - Neurocomputing, 2021 - Elsevier
In this paper, the H∞ state estimation problem is considered for a class of the discrete-time
delayed switched stochastic neural networks with sensor saturations. In order to improve the …
delayed switched stochastic neural networks with sensor saturations. In order to improve the …
Some novel approaches on state estimation of delayed neural networks
This paper studies the issue of state estimation for a class of neural networks (NNs) with time-
varying delay. A novel Lyapunov-Krasovskii functional (LKF) is constructed, where triple …
varying delay. A novel Lyapunov-Krasovskii functional (LKF) is constructed, where triple …
Adaptive sliding mode synchronization for a class of fractional-order chaotic systems with disturbance
S Shao, M Chen, X Yan - Nonlinear Dynamics, 2016 - Springer
This paper studies the fractional-order disturbance observer (FODO)-based adaptive sliding
mode synchronization control for a class of fractional-order chaotic systems with unknown …
mode synchronization control for a class of fractional-order chaotic systems with unknown …
Finite-time H∞ control for a class of Markovian jump systems with mode-dependent time-varying delays via new Lyapunov functionals
J Cheng, H Zhu, S Zhong, Y Zeng, X Dong - ISA transactions, 2013 - Elsevier
This paper is concerned with the problem of finite-time H∞ control for a class of Markovian
jump systems with mode-dependent time-varying delays via new Lyapunov functionals. In …
jump systems with mode-dependent time-varying delays via new Lyapunov functionals. In …
Design of extended dissipativity state estimation for generalized neural networks with mixed time-varying delay signals
This paper investigates the issue of extended dissipativity state estimation of generalized
neural networks (GNNs) with mixed time-varying delay signals. The integral terms in the time …
neural networks (GNNs) with mixed time-varying delay signals. The integral terms in the time …