Exponential Stability of Hysteresis Neural Networks with Varying Inputs

In this paper mathematical analysis of hysteresis neural network with varying inputs are proposed. Motivated by the application potential of the model we focus on existence, exponential stability and asymptotic equivalence of the networks. We establish sufficient conditions for exponential stability of this class of neural networks and this result can be applied through numerical example. The result improves the earlier publications due to the state convergence of the networks with neutral delays and varying inputs.