## SPIN Learning and Forgetting Surface Classifications with Dynamic Neural Networks

• This paper refers to the problem of adaptability over an infinite period of time, regarding dynamic networks. A never ending flow of examples have to be clustered, based on a distance measure. The developed model is based on the self-organizing feature maps of Kohonen [6], [7] and some adaptations by Fritzke [3]. The problem of dynamic surface classification is embedded in the SPIN project, where sub-symbolic abstractions, based on a 3-d scanned environment is being done.

Author: Uwe R. Zimmer, Ewald von Puttkamer, Herman Keuchel urn:nbn:de:hbz:386-kluedo-3006 Preprint English 1993 1993 Technische Universität Kaiserslautern 2000/04/03 ICANN 93, Amsterdam Fachbereich Informatik 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik Standard gemäß KLUEDO-Leitlinien vor dem 27.05.2011

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