Journal
NEURAL NETWORKS
Volume 73, Issue -, Pages 47-57Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2015.09.007
Keywords
Fractional-order neural networks; Time-varying delays; Global O(t(-alpha)) stability; S-asymptotically periodic solution; Globally S-asymptotic periodicity
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The present paper studies global O(t(-alpha)) stability and global asymptotical periodicity for a non-autonomous fractional-order neural networks with time-varying delays (FDNN). Firstly, some sufficient conditions are established to ensure that a non-autonomous FDNN is global O(t(-alpha)) stable based on a new Lyapunov function method and Leibniz rule for fractional differentiation. Next it is shown that the periodic or autonomous FDNN cannot generate exactly nonconstant periodic solution under any circumstances. Finally, we show that all solutions converge to a same periodic function for a periodic FDNN by using a fractional-order differential inequality technique. Our issues, methods and results are all new. (C) 2015 Elsevier Ltd. All rights reserved.
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