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Higher Order Neurodynamics of Associative Memory for Sequential Patterns

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5552))

Abstract

This paper describes higher order neurodynamics of associative memory for sequential patterns using a statistical method. First, the statistical analysis of direct correlations between the cross talk noise terms for higher order neural networks is made. Further, it is shown that storage capacities for k = 1, 2 and 3 dimensional cases are 0.263n, \(0.207\binom{n}{2}\) and \(0.180\binom{n}{3}\), respectively, where n is the number of neurons and \(\binom{n}{k}\) means the combination of k from n. The result for the one dimensional case is in fairly general agreement with Meir’s result, 0.269n, obtained by the replica theory.

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© 2009 Springer-Verlag Berlin Heidelberg

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Miyajima, H., Shigei, N., Yatsuki, S. (2009). Higher Order Neurodynamics of Associative Memory for Sequential Patterns. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_100

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  • DOI: https://doi.org/10.1007/978-3-642-01510-6_100

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01509-0

  • Online ISBN: 978-3-642-01510-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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