On the complexity of hierarchical associative memories

Authors:
Jana Štanclová
Affiliations:
Charles University in Prague, Prague, Czech Republic
Venue:
Proceedings of the 2009 ACM symposium on Applied Computing
Year:
2009

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Abstract

Associative memories represent a model of artificial neural networks applicable to the information storage and retrieval. However, the performance of traditional associative memories is very sensitive to the number of stored patterns and their mutual similarities. In order to avoid limitations imposed by processing larger amounts of mutually correlated patterns, we have developed the so-called Hierarchical Associative Memory (HAM) model. This paper is focused on the time complexity and memory complexity of the HAM model. The time complexity of the HAM model is derived. The memory complexity is analyzed and the theoretical results are compared with the experimental results.