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