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Neural Processing Letters

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01-12-2016

Finite-Time Boundedness Analysis of Memristive Neural Network with Time-Varying Delay

Authors: Hui Zhao, Lixiang Li, Haipeng Peng, Jinghua Xiao, Yixian Yang

Published in: Neural Processing Letters | Issue 3/2016

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Abstract

This paper considers the issue of the finite-time boundedness (FTB) of memristive neural network (MNN) with time-varying delay. It is known that the parameters of MNN are state dependent, the system stability of MNN via the classical analytical techniques is not realized directly. Hence, a novel technique is first developed to transform the MNN into the form of neural network with uncertain parameters in the paper. Further by introducing the appropriate Lyapunov function and the concept of FTB, a new method is proposed to guarantee that the state trajectory remains in a bounded region of the state space over a given finite-time interval. Finally, two numerical examples are given to illustrate the effectiveness of our proposed approaches.

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Title: Finite-Time Boundedness Analysis of Memristive Neural Network with Time-Varying Delay
Authors: Hui Zhao
Lixiang Li
Haipeng Peng
Jinghua Xiao
Yixian Yang
Publication date: 01-12-2016
Publisher: Springer US
Published in: Neural Processing Letters / Issue 3/2016
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI: https://doi.org/10.1007/s11063-015-9487-5

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