Open AccessAnti-periodic solutions for fractional-order bidirectional associative memory neural networks with delays
Author(s) -
Münevver Tuz,
Gülden Altay Suroğlu
Publication year - 2019
Publication title -
thermal science/thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci190805406t
Subject(s) - bidirectional associative memory , artificial neural network , content addressable memory , computer science , associative property , order (exchange) , stability (learning theory) , exponential stability , control theory (sociology) , mathematics , nonlinear system , artificial intelligence , pure mathematics , machine learning , physics , control (management) , finance , quantum mechanics , economics
This paper concerns fractional-order bidirectional associative memory neural networks with distributed delays. Based on inequality technique and Lyapunov functional method, some novel sufficient conditions are obtained for the existence and exponential stability of anti-periodic solutions are established. An example is given to show the feasibility main results.