Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6178
Title: A Type 2 Neuron Model for Classification and Regression Problems
Authors: Efe, Mehmet Önder
Keywords: type 2 neuron model
type 2 neural networks
Issue Date: 2009
Publisher: IEEE
Source: 4th International IEEE/EMBS Conference on Neural Engineering -- APR 29-MAY 02, 2009 -- Antalya, TURKEY
Series/Report no.: International IEEE EMBS Conference on Neural Engineering
Abstract: Type 2 fuzzy systems have been under investigation for a while and the projection of type 2 understanding for uncertainty management onto the connectionist models -i.e. neural networks- seems an interesting field of research. This paper considers neurons having multiple bias values defining a new structure that resembles the uncertainty handling capability of type 2 fuzzy models. Such a neuron provides many activation levels that are combined to obtain the neuron response. A neural network with this new model is presented. Several simulation results are shown and the universal approximation property is emphasized.
URI: https://hdl.handle.net/20.500.11851/6178
ISBN: 978-1-4244-2072-8
ISSN: 1948-3546
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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