Title :
Periodic Oscillation for Cohen-Grossberg-Type Bidirectional Associative Memory Neural Networks with Neutral Time-Varying Delays
Author_Institution :
Dept. of Math., Huaiyin Teachers´´ Coll., Huaiyin, China
Abstract :
In this paper, a model describing dynamics of Cohen-Grossberg-type bidirectional associative memory neural networks with neutral time-varying delays is investigated by using the continuation theorem of Mawhin´s coincidence degree theory and the properties of an M-matrix. Without assuming the continuous differentiability of time-varying delays, some sufficient conditions on the existence of the periodic solutions are obtained. The result of this paper is new and extent previously known result. Finally, an illustrative example is given to show the effectiveness of the obtained result.
Keywords :
content-addressable storage; delays; matrix algebra; neural nets; time-varying systems; Cohen-Grossberg-type bidirectional associative memory neural networks; M-matrix; Mawhin coincidence degree theory; continuation theorem; neutral time-varying delays; periodic oscillation; Associative memory; Computer networks; Delay effects; Educational institutions; Hopfield neural networks; Mathematical model; Mathematics; Neural networks; Signal processing; Sufficient conditions;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.630
