Numerical simulation of periodic solutions for a class of numerical discretization neural networks

Chun Lu; Xiaohua Ding; Mingzhu Liu

doi:10.1016/j.mcm.2010.03.005

Numerical simulation of periodic solutions for a class of numerical discretization neural networks

Chun Lu^*
, Xiaohua Ding
, Mingzhu Liu

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

In this paper, the existence and global exponential stability of periodic solutions for a class of numerical discretization neural networks are investigated. Using coincidence degree theory and the Lyapunov method, sufficient conditions for the existence and global exponential stability of periodic solutions are obtained. Numerical simulations are given at the end of this paper.

Original language	English
Pages (from-to)	386-396
Number of pages	11
Journal	Mathematical and Computer Modelling
Volume	52
Issue number	1-2
DOIs	https://doi.org/10.1016/j.mcm.2010.03.005
State	Published - Jul 2010
Externally published	Yes

Keywords

Coincidence degree
Globally exponentially stable
Lyapunov function
Neural network
Periodic solution

Access to Document

10.1016/j.mcm.2010.03.005

Cite this

@article{41c522df3e744a8498c459ea61c81129,

title = "Numerical simulation of periodic solutions for a class of numerical discretization neural networks",

abstract = "In this paper, the existence and global exponential stability of periodic solutions for a class of numerical discretization neural networks are investigated. Using coincidence degree theory and the Lyapunov method, sufficient conditions for the existence and global exponential stability of periodic solutions are obtained. Numerical simulations are given at the end of this paper.",

keywords = "Coincidence degree, Globally exponentially stable, Lyapunov function, Neural network, Periodic solution",

author = "Chun Lu and Xiaohua Ding and Mingzhu Liu",

year = "2010",

month = jul,

doi = "10.1016/j.mcm.2010.03.005",

language = "英语",

volume = "52",

pages = "386--396",

journal = "Mathematical and Computer Modelling",

issn = "0895-7177",

publisher = "Elsevier Ltd",

number = "1-2",

}

TY - JOUR

T1 - Numerical simulation of periodic solutions for a class of numerical discretization neural networks

AU - Lu, Chun

AU - Ding, Xiaohua

AU - Liu, Mingzhu

PY - 2010/7

Y1 - 2010/7

N2 - In this paper, the existence and global exponential stability of periodic solutions for a class of numerical discretization neural networks are investigated. Using coincidence degree theory and the Lyapunov method, sufficient conditions for the existence and global exponential stability of periodic solutions are obtained. Numerical simulations are given at the end of this paper.

AB - In this paper, the existence and global exponential stability of periodic solutions for a class of numerical discretization neural networks are investigated. Using coincidence degree theory and the Lyapunov method, sufficient conditions for the existence and global exponential stability of periodic solutions are obtained. Numerical simulations are given at the end of this paper.

KW - Coincidence degree

KW - Globally exponentially stable

KW - Lyapunov function

KW - Neural network

KW - Periodic solution

UR - https://www.scopus.com/pages/publications/77953133714

U2 - 10.1016/j.mcm.2010.03.005

DO - 10.1016/j.mcm.2010.03.005

M3 - 文章

AN - SCOPUS:77953133714

SN - 0895-7177

VL - 52

SP - 386

EP - 396

JO - Mathematical and Computer Modelling

JF - Mathematical and Computer Modelling

IS - 1-2

ER -

Numerical simulation of periodic solutions for a class of numerical discretization neural networks

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this