Title :
New stability conditions for BAM neural networks with time delays
Author :
Wu, Zhongfu ; Liao, Xiaofeng
Author_Institution :
Fac. of Comput., Chongqing Univ., China
Abstract :
In this paper, the Bi-directional Associative Memory (BAM) neural network with axonal signal transmission delay (DBAM) is considered. By combining a number of different Lyapunov functionals with the Razumikhin technique, some sufficient conditions for the existence of unique equilibrium and globally asymptotic stability are derived. These results are fairly general and can be verified easily. Besides, our approach for the analysis allows us to consider several different types of activation functions, including piecewise linear sigmoids with bounded activations as well as the usual C1-smooth sigmoids. We believe that the results obtained have considerable significance in the design and application of the BAM neural network
Keywords :
Lyapunov methods; asymptotic stability; content-addressable storage; delays; neural nets; piecewise linear techniques; stability criteria; BAM neural networks; C1-smooth sigmoids; Lyapunov functionals; Razumikhin technique; activation functions; axonal signal transmission delay; bi-directional associative memory neural network; bounded activations; globally asymptotic stability; piecewise linear sigmoids; stability conditions; time delays; unique equilibrium; Artificial neural networks; Associative memory; Asymptotic stability; Computer networks; Delay effects; Lyapunov method; Magnesium compounds; Neural networks; Neurons; Sufficient conditions;
Conference_Titel :
Circuits and Systems, 2000. IEEE APCCAS 2000. The 2000 IEEE Asia-Pacific Conference on
Conference_Location :
Tianjin
Print_ISBN :
0-7803-6253-5
DOI :
10.1109/APCCAS.2000.913500
