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Degree:Doctorate
Status:退休
School/Department:物理与电子信息工程学院

蔡秀珊

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Gender:Female

Education Level:Graduate student graduate

Alma Mater:上海交通大学

Paper achievements

Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality.
Date of Publication:2013-01-01 Hits:

First Author:Liu, Yang
Date of Publication:2013-01-01
Journal:Int. J. Appl. Math. Comput. Sci.
Affiliation of Author(s):数理与信息工程学院
Document Type:期刊
Volume:Vol.23
Issue:No.1
Page Number: 201-211
ISSN No.:1641-876X;2083-8492
Key Words:impulsive differential inequality;globally exponential stability;high-order Hopfield-type neural network
Abstract:This paper is devoted to studying the globally exponential stability of impulsive high-order Hopfield-type neural networks with time-varying delays. In the process of impulsive effect, nonlinear and delayed factors are simultaneously considered. A new imp
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