Abstract of FKI-168-92

Document-Name:  fki-168-92.ps.gz
Title:          Classification of Trajectories - Extracting Invariants
                with a Neural Network 
Authors:        Margit Kinder 
                Wilfried Brauer
Revision-Date:  1992/03/20
Category:       Technical Report (Forschungsberichte Künstliche Intelligenz)
Abstract:       A neural classifier of planar trajectories is presented.
		There already exist a large variety of classifiers that are
		specialized on particular invariants contained in a trajectory 
		classification task such as position-invariance, rotation-
                invariance, size-invariance, ... .
		That is, there exist classifiers specialized on recognizing
		trajectories e.g. independently of their position.
		The neural classifier presented in this paper is not 
                restricted to certain invariants in a task: The neural network
                itself extracts	the invariants contained in a classification 
                task by assessing only the trajectories. The trajectories need
                to be given as a set of points. No additional information must
                be available for training, which saves the designer from 
                determining the needed invariants by himself.
		Besides its applicability to real-world problems, such a more
		general classifier is also cognitively plausible: 
		In assessing trajectories for classification, human beings are
                able to	find class specific features, no matter what kinds of 
                invariants they are confronted with. Invariants are easily 
                handled by ignoring unspecific features.
Keywords:       invariant representation; task-dependant similarity measure;
		topological, distributed encoding; Wickelfeatures;
		tuple coding; delta rule; perceptron
Size:           10 pages
Language:       English
ISSN:           0941-6358
Copyright:      The ``Forschungsberichte Künstliche Intelligenz''
                series includes primarily preliminary publications,
                specialized partial results, and supplementary
                material. In the interest of a subsequent final
                publication these reports should not be copied. All
                rights and the responsability for the contents of the
                report are with the authors, which would appreciate
                critical comments.




Gerhard Weiss