Nonsmooth finite-time stabilization of neural networks with discontinuous activations

Title
Nonsmooth finite-time stabilization of neural networks with discontinuous activations
Author(s)
박주현X. Liu[X. Liu]N. Jiang[N. Jiang]J. Cao[J. Cao]
Keywords
DYNAMICAL NETWORKS; VARYING DELAYS; EXPONENTIAL STABILITY; SYSTEMS; SYNCHRONIZATION; CONSENSUS; CRITERIA; DISCRETE
Issue Date
201404
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Citation
NEURAL NETWORKS, v.52, pp.25 - 32
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. (C) 2014 Elsevier Ltd. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/32552http://dx.doi.org/10.1016/j.neunet.2014.01.004
ISSN
0893-6080
Appears in Collections:
공과대학 > 전기공학과 > Articles
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