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Dimension reduction in representation of the data

Abstract

Suppose the data consist of a set SS of points xjx_j, 1jJ1\leq j \leq J, distributed in a bounded domain DRND\subset R^N, where NN is a large number. An algorithm is given for finding the sets LkL_k of dimension kNk\ll N, k=1,2,...Kk=1,2,...K, in a neighborhood of which maximal amount of points xjSx_j\in S lie. The algorithm is different from PCA (principal component analysis)

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