Abstract: Grouping information problem appears in application in two main forms. These are the problem of recovering function, represented by its observations and the problem of classification (clusterization).It is very important for both them which are the ”representatives” of the objects under investigations: scalars, vectors or objects of other kinds. This choice is determined by the math technique can be used for handling with the “representatives”. Using the real valued vectors and Euclidean spaces correspondingly is therefore usual. Development of the technique, including SVD and Moore-Penrose? inversion on the base of special “cortege operators” for Euclidean space of Rmn type, is proposed in the article

Keywords: Feature vectors, information aggregating, generalized artificial neuronets, vector corteges, matrix corteges, linear operator between cortege spaces, Single Valued Decomposition for cortege linear operators.

ACM Classification Keywords: G.2.m. Discrete mathematics: miscellaneous,G.2.1 Combinatorics. G.3 Probability and statistics, G.1.6. Numerical analysis I.5.1.Pattern Recognition H.1.m. Models and Principles: miscellaneous:

Link:

VECTORS AND MATRIXES IN GROUPING INFORMATION PROBLEM

Donchenko V.

http://www.foibg.com/ijita/vol20/ijita20-02-p01.pdf