Título: Uma Técnica para a Redução da Cardinalidade de Padrões de Entrada de uma Rede Neural Artificial
Autores: Galvão, Roberto K. H.; Saldanha, Teresa C. B.; Yoneyama, Takashi; Araújo, Mário César U. de
Resumo: This paper proposes a new technique for reducing the cardinality of input patterns of artificial neural networks. The algorithm, denominated “Successive Projections” (SPA ), tries to extract, from a set of vectors, a subset whose elements are maximally independent. Beginning from a conveniently chosen point, the SPA pick s, at each step, the vector which has the largest projection in the subspace orthogonal to the vectors already selected. The technique was applied to the problem of choosing the best wavelengths for Simultaneous Multicomponent Analy sis via Molecular Ab sorption Spectrophotometry. The prediction capability of the resulting model is similar to that of models employing Principal Component Analysis. However, due to the Parsimony Principle, the model obtained via SPA may be indicated as more adequate.
Artigo em pdf: 4cbrn_029.pdf
Arquivo BibTex: 4cbrn_029.bib