DocumentCode
1749050
Title
Multilayer feedforward weight initialization
Author
Hernández-Espinosa, Carlos ; Fernández-Redondo, Mercedes
Author_Institution
Univ. Jaume I, Castellon, Spain
Volume
1
fYear
2001
fDate
2001
Firstpage
166
Abstract
We present the results of an experimental comparison among seven different weight initialization methods in twelve different problems. The comparison is performed by measuring the speed of convergence, the generalization capability and the probability of successful convergence. It is not usual to find an evaluation of the three properties in the literature on weight initialization. The training algorithm was backpropagation with a hyperbolic tangent transfer function. We found that the performance can be improved with respect to the usual initialization scheme
Keywords
backpropagation; convergence; feedforward neural nets; generalisation (artificial intelligence); transfer functions; backpropagation; convergence; feedforward neural network; generalization; learning algorithm; network performance; transfer function; weight initialization; Backpropagation algorithms; Bibliographies; Convergence; Equations; Neural networks; Nonhomogeneous media; Performance evaluation; Transfer functions; Velocity measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-7044-9
Type
conf
DOI
10.1109/IJCNN.2001.939011
Filename
939011
Link To Document