Nonsmooth finite-time stabilization of neural networks with discontinuous activations

Authors:
Xiaoyang Liu;Ju H. Park;Nan Jiang;Jinde Cao
Affiliations:
-;-;-;-
Venue:
Neural Networks
Year:
2014

Citing 11
Cited 0

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Abstract

This paper is concerned with the finite-time stabilization for a class of neural networks (NNs) with discontinuous activations. The purpose of the addressed problem is to design a discontinuous controller to stabilize the states of such neural networks in finite time. Unlike the previous works, such stabilization objective will be realized for neural networks when the activations and controllers are both discontinuous. Based on the famous finite-time stability theorem of nonlinear systems and nonsmooth analysis in mathematics, sufficient conditions are established to ensure the finite-time stability of the dynamics of NNs. Then, the upper bound of the settling time for stabilization can be estimated in two forms due to two different methods of proof. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design method.