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On sequential nonlinear mapping for data structure analysis
Volume 6, Issue 2 (1995), pp. 225–232
Algirdas Mykolas Montvilas  

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https://doi.org/10.3233/INF-1995-6205
Pub. online: 1 January 1995      Type: Research Article     

Published
1 January 1995

Abstract

An algorithm for the sequential analysis of multivariate data structure is presented. The algorithm is based on the sequential nonlinear mapping of L-dimensional vectors from the L-hyperspace into a lower-dimensional (two-dimensional) vectors such that the inner structure of distances among the vectors is preserved. Expressions for the sequential nonlinear mapping are obtained. The mapping error function is chosen. Theoretical minimum amount of the very beginning simultaneously mapped vectors is obtained.

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Keywords
dimensionality reduction sequential nonlinear mapping sequential detection of changes

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INFORMATICA

  • Online ISSN: 1822-8844
  • Print ISSN: 0868-4952
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