Title :
Stability analysis of the class of delayed neural networks
Author :
Arik, Sabri ; Tavsanoglu, Vedat
Author_Institution :
Dept. of Electron., Istanbul Univ., Turkey
Abstract :
In this paper, we derive several sufficient conditions for the asymptotic stability of delayed neural networks. These conditions ensure the asymptotic stability of the equilibrium point of a delayed neural network independently of the delay parameter. The results obtained impose constraint conditions on the interconnection matrix of the neural system
Keywords :
asymptotic stability; delays; neural nets; asymptotic stability; constraint conditions; delay parameter; delayed neural networks; equilibrium point; interconnection matrix; stability analysis; Asymptotic stability; Equations; Erbium; Hopfield neural networks; Neural networks; Neurons; Stability analysis; Sufficient conditions;
Conference_Titel :
Circuits and Systems, 1999. ISCAS '99. Proceedings of the 1999 IEEE International Symposium on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-5471-0
DOI :
10.1109/ISCAS.1999.777637
