On sequential nonlinear mapping for data structure analysis
Volume 6, Issue 2 (1995), pp. 225–232
Pub. online: 1 January 1995
Type: Research Article
Published
1 January 1995
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.