A new class of interval projection neural networks for solving interval quadratic program

Ke Ding and Nan-Jing Huang

Chaos, Solitons & Fractals, 2008, vol. 35, issue 4, 718-725

Abstract: In this paper, a new class of interval projection neural networks are introduced and studied, the equilibrium point of this neural networks is equivalent to the KT point of a class of interval quadratic program. By using fixed point theorem and constructing suitable Lyapunov functions, we obtain sufficient conditions to ensure the existence and global exponential stability for the unique equilibrium point of interval projection neural networks. In the last section, we give an example to illustrate the validity of our results.

Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:35:y:2008:i:4:p:718-725

DOI: 10.1016/j.chaos.2006.05.037

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