期刊
NEURAL NETWORKS
卷 15, 期 10, 页码 1185-1196出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0893-6080(02)00091-6
关键词
non-Euclidean data sets; monotonic embedding; multidimensional scaling; singular Cholesky factor; spatial maps
This paper presents a fast incremental algorithm for embedding data sets belonging to various topological spaces in Euclidean spaces. This is useful for networks whose input consists of non-Euclidean (possibly non-numerical) data, for the on-line computation of spatial maps in autonomous agent navigation problems, and for building internal representations from empirical similarity data. (C) 2002 Elsevier Science Ltd. All rights reserved.
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