Partial stabilization of stochastic hybrid neural networks driven by Lévy noise

Abstract

The paper tackles the stabilization of stochastic hybrid neural networks. Different from the existing work which the Brownian motion was used to stabilize neural networks for the stochastic stability, the stabilization is generalized by Lévy noise in this paper. To address the unobservable items in the hybrid neural networks, we introduce the Markov chain into the hybrid neural networks and divide the state space of Markov chain into two subsets for observable and unobservable items. Then, the sufficient conditions of stabilization and destabilization for the stochastic neural networks are obtained.