Abstract of FKI-183-93

Document-Name:  fki-183-93.ps.gz
Title:   	Theoretical Issues Concerning the Representation of
                Continuous-Valued Input and Output Data in Neural
Autors:     	Margit Kinder 
                Till Brychcy  
Revision Date:	June, 1993
Category:	Technical Report (Forschungsberichte Künstliche Intelligenz)
Abstract:	There exist all kinds of problems where both input and output 
                data for neural networks are continuous and vector-valued.
                From our previous works we know that distributed representa-
                tions of the input data are extremely useful for neural net-
                works to embody good generalization skills and also to model 
                forbidden regions in data space. Units are only located in
                those regions where data has occurred in the learning process.
                In this paper, we analyze Kohonen's self-organizing feature 
                maps with respect to distributed representations and in this 
                respect come up with a comparison to Radial Basis Functions.
                Concerning the output data, we give two interpretations for 
                distributed representations. First, the center of
                gravity interpretation for which we explain some severe 
                problems. Second, the pseudo-inverse of the matrix defined by 
                the positions of the representation units.
Keywords:	self-organizing feature maps; function approximation;
        	pseudo-inverse; normalization of input vectors;
	        topologically distributed representation; Radial Basis 
Size:   	8 pages
Language:	English
ISSN:     	0941-6358
Copyright:      The ``Forschungsberichte Künstliche Intelligenz''
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Gerhard Weiss