Graph-based normalization and whitening for non-linear data analysis

In this paper we construct a graph-based normalization algorithm for non-linear data analysis. The principle of this algorithm is to get a spherical average neighborhood with unit radius. First we present a class of global dispersion measures used for “global normalization”; we then adapt these meas...

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Vydané v:	Neural networks Ročník 19; číslo 6; s. 864 - 876
Hlavný autor:	Aaron, Catherine
Médium:	Journal Article Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	Oxford Elsevier Ltd 01.07.2006 Elsevier Science Elsevier
Predmet:	Algorithms Applied sciences Artificial Intelligence Cluster Analysis Computer Graphics Computer science; control theory; systems Connectionism. Neural networks Exact sciences and technology Geodesic distance Graph Humans Mathematics Models, Statistical Nonlinear Dynamics Normalization Other Statistics SOM Statistics SOM Normalization Graph Geodesic distance Data analysis Procedure call Multigraph Geodesic structure Neural network Algorithm Weighted graph Self-organising feature maps Geodesic Analogy Dispersion measure normalization graph geodesic distance
ISSN:	0893-6080, 1879-2782
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