Exponential stability analysis of stochastic delayed cellular neural network

Dynamic Analysis of Stochastic Recurrent Neural Networks

“…We can find the recent papers [9,11,19,21,24] in this direction. However, it is assumed in [9,21,24] that all connections and delays are constants, the activation functions appear in [9] are bounded, the delay functions appear in [19] are differential and their derivatives are simultaneously required to be not greater than 1, and the connections appear in [11] are constants. Obviously, these requirements are relaxed in our results.…”

New Delay-Interval-Dependent Exponential Stability for Stochastic Neural Networks with Interval Time-Varying Delay and Distributed Delay

“…For example, delay-independent and delay-dependent global asymptotic stability conditions in mean square for different classes of stochastic delayed neural networks were reported in [1] and [8,21], respectively. When faster convergence was considered, the topic of global exponential stability in mean square for stochastic delayed neural networks was investigated in [7,22,40]. In addition, the robust asymptotic and exponential stability problem in mean square for stochastic neural networks with time delays and uncertainties have been investigated in [2, 9, 11-14, 24, 29, 33, 34], respectively.…”

Exponential stability analysis for delayed stochastic Cohen-Grossberg neural network

“…Results in 5,6 suggested that the neural networks can be stabilized or destabilized by certain stochastic inputs, which implies that it is important to consider the noise effects in the stability analysis for the neural networks. Recently, the study of stochastic neural networks has drawn much attentions from researchers all over the world and some results can be found in 7,8,9,10,11,12,13,22 and the references cited therein 15,16,17,19,21 . But for the study of stochastic CGNN, up till now, there are only a few results 10,11,14,20 .…”