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.
Keywords
- Genetic Algorithm
- Exchange Algorithm
- Alternative Tool
- Minimax Approximation
- Minimax Sense
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Kuri-Morales, A.F., Juárez-Almaraz, F. (2005). Genetic Multivariate Polynomials: An Alternative Tool to Neural Networks. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_28
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DOI: https://doi.org/10.1007/11578079_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
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