A geometric approach to the problem of reconstruction of the sample behavior in hidden dimensions
| Autor: | A. P. Vinogradov, Yu. P. Laptin |
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| Rok vydání: | 2010 |
| Předmět: |
Mathematical optimization
Uniform distribution (continuous) Dimension (vector space) Sampling (statistics) A priori and a posteriori Cluster sampling Sample (statistics) Computer Vision and Pattern Recognition Computer Graphics and Computer-Aided Design Empirical distribution function Algorithm Manifold Mathematics |
| Zdroj: | Pattern Recognition and Image Analysis. 20:479-483 |
| ISSN: | 1555-6212 1054-6618 |
| DOI: | 10.1134/s1054661810040085 |
| Popis: | We investigate a direct geometric approach to the problem of reconstruction of the behavior of a sample of hidden dimensions. A method for an improved description of cluster sampling, based on the interpretation of nonlinearities in the empirical distribution of both local projections of a uniform distribution on a smooth manifold, defined in the hidden dimension, is given. This method can be used to resolve a number of critical features in the empirical distributions. The a priori assumptions under which many variants of reconstruction of sampling behavior in the hidden dimensions are limited are considered. |
| Databáze: | OpenAIRE |
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