Geometric Associative Processing Applied to Pattern Classification

Authors:
Benjamín Cruz;Humberto Sossa;Ricardo Barrón
Affiliations:
Center for Computer Research, National Polytechnic Institute, Mexico City, Mexico 07738;Center for Computer Research, National Polytechnic Institute, Mexico City, Mexico 07738;Center for Computer Research, National Polytechnic Institute, Mexico City, Mexico 07738
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Year:
2009

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Abstract

Associative memories (AM's) have been extensively used during the last 40 years for pattern classification and pattern restoration. In this paper Conformal Geometric Algebra (CGA) is used to develop a new associative memory (AM). The proposed AM makes use of CGA and quadratic programming to store associations among patterns and their respective classes. An unknown pattern is classified by applying an inner product between the pattern and the build AM. Numerical and real examples are presented to show the potential of the proposal.