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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Bibliographic Details
Published in:	Neural networks Vol. 19; no. 6; pp. 864 - 876
Main Author:	Aaron, Catherine
Format:	Journal Article Conference Proceeding
Language:	English
Published:	Oxford Elsevier Ltd 01.07.2006 Elsevier Science Elsevier
Subjects:	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
Online Access:	Get full text
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