Delay-independent stability in bidirectional associative memory networks
K Gopalsamy, XZ He - IEEE Transactions on Neural Networks, 1994 - ieeexplore.ieee.org
K Gopalsamy, XZ He
IEEE Transactions on Neural Networks, 1994•ieeexplore.ieee.orgIt 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.<>
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.<>
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.< >
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