Open AccessExistence and global exponential stability of periodic solution of high-order Cohen-Grossberg neural network with impulses
Author(s) -
Jing Liu
Publication year - 2009
Publication title -
demonstratio mathematica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.541
H-Index - 28
eISSN - 2391-4661
pISSN - 0420-1213
DOI - 10.1515/dema-2013-0154
Subject(s) - coincidence , mathematics , exponential stability , degree (music) , artificial neural network , stability (learning theory) , order (exchange) , exponential function , mathematical analysis , computer science , nonlinear system , artificial intelligence , machine learning , physics , medicine , alternative medicine , finance , pathology , quantum mechanics , acoustics , economics
Sufficient conditions are obtained for the existence and global exponential stability of periodic solution of high-order Cohen-Grossberg neural network with impulses by using Mawhin’s continuation theorem of coincidence degree and by means of a method based differential inequality.