Titlebook: Computational Intelligence Based on Lattice Theory; Vassilis G. Kaburlasos,Gerhard X. Ritter Book 2007 Springer-Verlag Berlin Heidelberg 2

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Convex Coordinates From Lattice Independent Sets for Visual Pattern Recognitionhe data sample points. The features extracted are the coordinates of the data points relative to the extremal points, the convex coordinates. We have experimented this approach in several applications that will be summarized in the chapter.

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Application of Fuzzy Lattice Neurocomputing (FLN) in Ocean Satellite Images for Pattern Recognitionral networks. The results obtained by the fuzzy lattice system are clearly better than the results obtained by ANNs (Artificial Neural Nets), knowledge based reasoning systems, and graphic expert system (GES).

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Unmatched Jumps in the Limit Process,al effort to produce an optimal or a sub-optimal network. Furthermore, we compare the performance of GFAM, GEAM and GGAM with other competitive ARTMAP structures that have appeared in the literature and addressed the category proliferation problem in ART.

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More Stochastic-Process Limits,, and differential evolution can be used to weigh the importance of each attribute and that this weighting can provide additional improvements over simply using the similarity measure. We present experimental evidence that the proposed techniques imply significant improvements.

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1860-949X ntary material: A number of di?erent instruments for design can be uni?ed in the context of lattice theory towards cross-fertilization By“l(fā)atticetheory”[1]wemean,equivalently,eitherapartialordering relation [2,3]ora couple of binary algebraic operations [3, 4]. There is a growing interest in computa