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dc.contributor.authorKoetsier, Jos
dc.contributor.authorCorchado Rodríguez, Emilio Santiago 
dc.contributor.authorMacDonald, Donald
dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.contributor.authorFyfe, Colin
dc.identifier.citationLecture Notes in Computer Science Computational Science - ICCS 2004. Lecture Notes in Computer Science. Volumen 3037, pp. 650-653.
dc.identifier.isbn978-3-540-22115-9 (Print) / 978-3-540-24687-9 (Online)
dc.identifier.issn0302-9743 (Print) / 1611-3349 (Online)
dc.description.abstractWe present a novel method based on a recently proposed extension to a negative feedback network which uses simple Hebbian learning to self-organise called Maximum Likelihood Hebbian learning [2]. We use the kernel version of the ML algorithm on data from a spectroscopic analysis of a stained glass rose window in a Spanish cathedral. It is hoped that in classifying the origin and date of each segment it will help in the restoration of this and other historical stain glass windows.
dc.publisherSpringer Science + Business Media
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.subjectComputer Science
dc.titleKernel Maximum Likelihood Hebbian Learning

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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported