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, Tome 23 (2013), p. 201-211 / Harvested from The Polish Digital Mathematics Library

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.

Publié le : 2013-01-01
EUDML-ID : urn:eudml:doc:251305
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     author = {Yang Liu and Rongjiang Yang and Jianquan Lu and Bo Wu and Xiushan Cai},
     title = {Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality},
     journal = {International Journal of Applied Mathematics and Computer Science},
     volume = {23},
     year = {2013},
     pages = {201-211},
     zbl = {1293.93634},
     language = {en},
     url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv23z1p201bwm}
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Yang Liu; Rongjiang Yang; Jianquan Lu; Bo Wu; Xiushan Cai. Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality. International Journal of Applied Mathematics and Computer Science, Tome 23 (2013) pp. 201-211. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv23z1p201bwm/

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