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Exploiting the analogy between immunology and sparse distributed memory.

Hart, Emma; Ross, Peter

Authors

Peter Ross



Contributors

Jonathan Timmis
Editor

Peter J. Bentley
Editor

Abstract

The relationship between immunological memory and a class of associative memories known as sparse distributed memories (SDM) is well known. This paper proposes a new model for clustering non-stationary data based on a combination of salient features from the two metaphors. The resulting system embodies the important principles of both types of memory; it is self-organising, robust, scalable, dynamic and can perform anomaly detection. The model is rst applied to clustering static datasets, and is shown to outperform two other systems based on immunological principles. It is then applied to clustering non-stationary data-sets with promising results.

Citation

Hart, E., & Ross, P. (2002, September). Exploiting the analogy between immunology and sparse distributed memory. Presented at ICARIS 2002

Conference Name ICARIS 2002
Start Date Sep 9, 2002
End Date Sep 11, 2002
Publication Date 2002
Deposit Date Jun 4, 2010
Peer Reviewed Peer Reviewed
Pages 59-67
Book Title ICARIS 2002 : 1st International Conference on Artificial Immune Systems
ISBN 1902671325
Keywords Immunology; sparse distributed computing; clustering; non-stationery data;
Public URL http://researchrepository.napier.ac.uk/id/eprint/3311