Statistical neurodynamics for sequence processing neural networks with finite dilution

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Abstract

We extend the statistical neurodynamics to study transient dynamics of sequence processing neural networks with finite dilution, and the theoretical results are supported by extensive numerical simulations. It is found that the order parameter equations are completely equivalent to those of the Generating Functional Method, which means that crosstalk noise follows normal distribution even in the case of failure in retrieval process. In order to verify the gaussian assumption of crosstalk noise, we numerically obtain the cumulants of crosstalk noise, and third- and fourth-order cumulants are found to be indeed zero even in non-retrieval case. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Zhang, P., & Chen, Y. (2007). Statistical neurodynamics for sequence processing neural networks with finite dilution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4491 LNCS, pp. 1144–1152). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_134

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