Pattern classification based on conformal geometric algebra and optimization techniques

Benjamín Cruz, Ricardo Barrón, Humberto Sossa

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Conformal Geometric Algebra (CGA) is a high level language commonly used in mathematical, physics and engineering problems. At a top level, CGA is a free coordinate tool for designing and modeling geometric problems; at a low level CGA provides a new coordinate framework for numeric processing in problem solving. In this paper we show how to use quadratic programming and CGA for, given two sets p and q of points in ℝ n , construct an optimal separation sphere S such that, all points of p are contained inside of it, and all points of q are outside. To classify an unknown pattern x, an inner product must be applied between x and S. Some numerical and real examples to test the proposal are given.

Idioma originalInglés
Título de la publicación alojadaMICAI 2008
Subtítulo de la publicación alojadaAdvances in Artificial Intelligence - 7th Mexican International Conference on Artificial Intelligence, Proceedings
Páginas273-283
Número de páginas11
DOI
EstadoPublicada - 2008
Evento7th Mexican International Conference on Artificial Intelligence, MICAI 2008 - Atizapan de Zaragoza, México
Duración: 27 oct. 200831 oct. 2008

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen5317 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia7th Mexican International Conference on Artificial Intelligence, MICAI 2008
País/TerritorioMéxico
CiudadAtizapan de Zaragoza
Período27/10/0831/10/08

Huella

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