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Neural Computation

May 1993, Vol. 5, No. 3, Pages 463-472
(doi: 10.1162/neco.1993.5.3.463)
© 1993 Massachusetts Institute of Technology
The Characteristics of the Convergence Time of Associative Neural Networks
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The authors have analyzed the dynamics of associative neural networks based on macroscopic state equations and have shown that both a layered associative net and an autocorrelation type net have the same convergence property: If a recalling process succeeds, the network converges very fast to one of the memorized patterns. But if a recalling process fails, it converges very slowly to a spurious state or does not converge. This property was also checked by computer simulations on a large scale (N = 1000) neural network. Moreover, it is shown that the convergence time for a successful recall is of order log(N). If this convergence time difference is used, execution time and memory can be saved and it can be determined whether a recalling process succeeds or fails without any additional procedure.