DocumentCode
288364
Title
Optimization of activation functions in multilayer neural network applied to pattern classification
Author
Nakayama, Kenji ; KIMURA, Yoshinori
Author_Institution
Dept. of Electr. & Comput. Eng., Kanazawa Univ., Japan
Volume
1
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
431
Abstract
An optimization method of activation functions is proposed. Three typical functions are combined in hidden layers. Contribution of the functions is evaluated using three criteria. The useful functions, are selected or multiplied in the learning process. Problems of parity and of counting `1´ in bit-patterns can be solved by the proposed method with the suitable functions and the minimum number of hidden units
Keywords
backpropagation; multilayer perceptrons; optimisation; pattern classification; transfer functions; activation functions; counting; hidden layers; multilayer neural network; optimization method; parity; pattern classification; Backpropagation algorithms; Computer simulation; Design optimization; Electronic mail; Equations; Intelligent networks; Multi-layer neural network; Neural networks; Optimization methods; Pattern classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374201
Filename
374201
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