title: Straight monotonic embedding of data sets in Euclidean spaces.
abstract: 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.
authors.affiliation: Laboratoire de Psychologie Cognitive, CNRS-UMR 6146, Université de Provence, France. courrieu@up.univ-mrs.fr
authors.forename: Pierre
authors.initials: P
authors.lastname: Courrieu
mesh_terms: D000465:Algorithms; D005556:Form Perception / Q000502:physiology*; D016571:Neural Networks, Computer; D012371:Robotics