Straight monotonic embedding of data sets in Euclidean spaces
نویسنده
چکیده
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.
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ورودعنوان ژورنال:
- Neural networks : the official journal of the International Neural Network Society
دوره 15 10 شماره
صفحات -
تاریخ انتشار 2002