DocumentCode
2619652
Title
Capacity of associative memory
Author
Kuo, I-Chuan ; Zhang, Zhen
Author_Institution
Commun. Sci. Inst., Univ. of Southern California, Los Angeles, CA, USA
fYear
1994
fDate
27 Jun-1 Jul 1994
Firstpage
222
Abstract
It is well known that the second-order Hopfield associative memory has storage capacity of order O(n/log n) This result is proved under the assumption that the stored vectors and probe vector are subject to uniform distributions. Unfortunately, this is not always the case practically. We prove that the capacity drops to order of zero when stored vectors and probe vector have nonuniform distributions. Therefore, it is necessary to explore the influence of these distributions on the capacity. To improve the capacity of associative memory, the high-order Hopfield model was proposed by Psaltis, Park and Hong (1988) whose capacity is rigorously determined in this paper. As an alternative of the Hopfield associative memory, are introduce an s-order polynomial approximation of the projection rule and prove that its storage capacity is higher than that of the Hopfield associative memory with the same implementation complexity
Keywords
Hopfield neural nets; content-addressable storage; statistical analysis; Hopfield associative memory; associative memory capacity; high-order Hopfield model; implementation complexity; nonuniform distributions; polynomial approximation; probe vector; projection rule; second-order Hopfield associative memory; storage capacity; stored vectors; uniform distributions; Associative memory; Error analysis; Hamming distance; Information theory; Optical fiber networks; Polynomials; Probability distribution; Probes;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location
Trondheim
Print_ISBN
0-7803-2015-8
Type
conf
DOI
10.1109/ISIT.1994.394746
Filename
394746
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