Title :
A study of the generalization capability versus training in backpropagation neural networks
Author :
Dalianis, P.J. ; Tzafestas, S.G. ; Anthopoulos, G.
Author_Institution :
Div. of Comput. Sci., Nat. Tech. Univ. of Athens, Greece
Abstract :
The phenomenon of overtraining in backpropagation neural networks is discussed. The relationships between network size, training set size and generalization capabilities are examined. An extension to an existing algorithm of backpropagation is described. The extended algorithm provides a new energy function and its advantages, such as improved plasticity and performance, along with its dynamic properties, are explained. The algorithm is applied to some common problems and simulation results are presented and discussed
Keywords :
backpropagation; generalisation (artificial intelligence); inference mechanisms; multilayer perceptrons; BP algorithm; backpropagation neural networks; common problems; dynamic properties; energy function; generalization capabilities; generalization capability; multilayer feature-based neural networks; network size; overtraining; plasticity; simulation results; training; training set size; Backpropagation algorithms; Function approximation; Intelligent control; Intelligent networks; Intelligent robots; Multi-layer neural network; Neural networks; Robot control; Testing; Vectors;
Conference_Titel :
Systems, Man and Cybernetics, 1993. 'Systems Engineering in the Service of Humans', Conference Proceedings., International Conference on
Conference_Location :
Le Touquet
Print_ISBN :
0-7803-0911-1
DOI :
10.1109/ICSMC.1993.390760
