# Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality

Yang Liu; Rongjiang Yang; Jianquan Lu; Bo Wu; Xiushan Cai

International Journal of Applied Mathematics and Computer Science (2013)

- Volume: 23, Issue: 1, page 201-211
- ISSN: 1641-876X

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topYang Liu, et al. "Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality." International Journal of Applied Mathematics and Computer Science 23.1 (2013): 201-211. <http://eudml.org/doc/251305>.

@article{YangLiu2013,

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 impulsive differential inequality is derived based on the Lyapunov-Razumikhin method and some novel stability criteria are then given. These conditions, ensuring the global exponential stability, are simpler and less conservative than some of the previous results. Finally, two numerical examples are given to illustrate the advantages of the obtained results.},

author = {Yang Liu, Rongjiang Yang, Jianquan Lu, Bo Wu, Xiushan Cai},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {impulsive differential inequality; globally exponential stability; high-order Hopfield-type neural network},

language = {eng},

number = {1},

pages = {201-211},

title = {Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality},

url = {http://eudml.org/doc/251305},

volume = {23},

year = {2013},

}

TY - JOUR

AU - Yang Liu

AU - Rongjiang Yang

AU - Jianquan Lu

AU - Bo Wu

AU - Xiushan Cai

TI - Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality

JO - International Journal of Applied Mathematics and Computer Science

PY - 2013

VL - 23

IS - 1

SP - 201

EP - 211

AB - 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 impulsive differential inequality is derived based on the Lyapunov-Razumikhin method and some novel stability criteria are then given. These conditions, ensuring the global exponential stability, are simpler and less conservative than some of the previous results. Finally, two numerical examples are given to illustrate the advantages of the obtained results.

LA - eng

KW - impulsive differential inequality; globally exponential stability; high-order Hopfield-type neural network

UR - http://eudml.org/doc/251305

ER -

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