Exponential Stability of Neural Network with General Noise
The problem of exponential stability of neural network (NN) with general noise is considered in this article. The noise in our neural network model which can be a mixture of white and non-white noise is more suitable for real nervous systems than white noise. By utilizing the random analysis method and Lyapunov functional method techniques, we obtain the conditions of the exponential stability for neural network with general noise. Unlike the NN with white noise in the existing papers, which are modeled as stochastic differential equations, our model with general noise is based on the random differential equations. Finally, an illustrative example is presented to demonstrate the effectiveness and usefulness of the proposed results.
KeywordsExponential stability Neural networks General noise
This work was partially supported by the Natural Science Foundation of China (grant no. 61573095).
- 4.J. Zhou, X. Ding, L. Zhou, W. Zhou, J. Yang, D. Tong, Almost sure adaptive asymptotically synchronization for neutral-type multi-slave neural networks with Markovian jumping parameters and stochastic perturbation. Neurocomputing 214(19), 44–52 (2016)Google Scholar