Presentation 2002/3/12
Utilization of a Modular-Type Neural Network with Nonlinear Transformation for Pattern Recognition Problems
K. MORISHIMA, S. SATOH, M. SHIMOMURA, S. MIYAKE, H. ASO,
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Abstract(in English) A modular-type neural network is proposed in order to solve pattern recognition problems. Neurons in the hidden layer convert an input space to a curved space by use of polynominal functions, and a neuron in the output makes discriminant surfaces by RBF(Radial Basis Functions). The proposed network is able to recognize patterns whose distribution of the features are non-super-ellipsoids. We show that the network has ability to make a multiple discriminant surface, that is, multi-templates are generated automatically. Numeral simulations show that the network works successfully for different distributions of input: i) non-super-elliptic distribution, ii) concave distribution, iii) spatially separated distribution. We evaluate the network for The Monk's problem.
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Keyword(in English) modular-type neural network / RBF / nonlinear transformation / pattern recognition
Paper # NC2001-180
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Committee NC
Conference Date 2002/3/12(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Utilization of a Modular-Type Neural Network with Nonlinear Transformation for Pattern Recognition Problems
Sub Title (in English)
Keyword(1) modular-type neural network
Keyword(2) RBF
Keyword(3) nonlinear transformation
Keyword(4) pattern recognition
1st Author's Name K. MORISHIMA
1st Author's Affiliation Department of Electrical and Communication Engineering, Graduate School of Engineering,Tohoku University()
2nd Author's Name S. SATOH
2nd Author's Affiliation Department of Applied Physics, Graduate School of Engineering, Tohoku University
3rd Author's Name M. SHIMOMURA
3rd Author's Affiliation Department of Electrical and Communication Engineering, Graduate School of Engineering,Tohoku University
4th Author's Name S. MIYAKE
4th Author's Affiliation Department of Applied Physics, Graduate School of Engineering, Tohoku University
5th Author's Name H. ASO
5th Author's Affiliation Department of Electrical and Communication Engineering, Graduate School of Engineering,Tohoku University
Date 2002/3/12
Paper # NC2001-180
Volume (vol) vol.101
Number (no) 736
Page pp.pp.-
#Pages 8
Date of Issue