Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Brief paper: Razumikhin-type stability theorems for discrete delay systems
Automatica (Journal of IFAC)
Brief paper: Stability analysis for discrete-time switched time-delay systems
Automatica (Journal of IFAC)
Almost sure exponential stability of recurrent neural networks with Markovian switching
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Automatica (Journal of IFAC)
IEEE Transactions on Neural Networks
New passivity analysis for neural networks with discrete and distributed delays
IEEE Transactions on Neural Networks
Brief paper: Stability analysis of switched stochastic systems
Automatica (Journal of IFAC)
Stability analysis and stabilization control of multi-variable switched stochastic systems
Automatica (Journal of IFAC)
IEEE Transactions on Neural Networks
Adaptive probabilistic neural networks for pattern classification in time-varying environment
IEEE Transactions on Neural Networks
Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays
IEEE Transactions on Neural Networks
Motif discoveries in unaligned molecular sequences using self-organizing neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Robust Synchronization of an Array of Coupled Stochastic Discrete-Time Delayed Neural Networks
IEEE Transactions on Neural Networks
Convergence Dynamics of Stochastic Cohen–Grossberg Neural Networks With Unbounded Distributed Delays
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Delay-Dependent Stability Analysis for Switched Neural Networks With Time-Varying Delay
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Constrained Evolutionary Computation Method for Detecting Controlling Regions of Cortical Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Multiobjective Identification of Controlling Areas in Neuronal Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
| Hi-index | 0.00 |
This paper is concerned with the global exponential stability of switched stochastic neural networks with time-varying delays. Firstly, the stability of switched stochastic delayed neural networks with stable subsystems is investigated by utilizing the mathematical induction method, the piecewise Lyapunov function and the average dwell time approach. Secondly, by utilizing the extended comparison principle from impulsive systems, the stability of stochastic switched delayed neural networks with both stable and unstable subsystems is analyzed and several easy to verify conditions are derived to ensure the exponential mean square stability of switched delayed neural networks with stochastic disturbances. The effectiveness of the proposed results is illustrated by two simulation examples.