Title :
Delay-independent stability in bidirectional associative memory networks
Author :
Gopalsamy, K. ; He, Xue-Zhong
Author_Institution :
Sch. of Inf. Sci. & Technol., Flinders Univ. South Australia, Adelaide, SA, Australia
fDate :
11/1/1994 12:00:00 AM
Abstract :
It is shown that if the neuronal gains are small compared with the synaptic connection weights, then a bidirectional associative memory network with axonal signal transmission delays converges to the equilibria associated with exogenous inputs to the network. Both discrete and continuously distributed delays are considered; the asymptotic stability is global in the state space of neuronal activations and also is independent of the delays
Keywords :
content-addressable storage; delays; neural nets; stability; state-space methods; asymptotic stability; axonal signal transmission delays; bidirectional associative memory networks; continuously distributed delays; discrete delays; neuronal gains; state space; synaptic connection weights; Associative memory; Asymptotic stability; Australia; Circuit stability; Helium; Information science; Intelligent networks; Lyapunov method; Neurons; State-space methods;
Journal_Title :
Neural Networks, IEEE Transactions on
