Genetic multivariate polynomials: an alternative tool to neural networks

Authors:
Angel Fernando Kuri-Morales;Federico Juárez-Almaraz
Affiliations:
Instituto Tecnológico Autónomo de, México;Universidad Nacional Autónoma de México Río, D.F., México
Venue:
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
Year:
2005

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Abstract

One of the basic problems of applied mathematics is to find a synthetic expression (model) which captures the essence of a system given a (necessarily) finite sample which reflects selected characteristics. When the model considers several independent variables its mathematical treatment may become burdensome or even downright impossible from a practical standpoint.