DocumentCode
1842633
Title
Efficient algorithm for training neural networks with one hidden layer
Author
Wilamowski, Bogdan M. ; Chen, Yixin ; Malinowski, Aleksander
Author_Institution
Dept. of EE, Wyoming Univ., Laramie, WY, USA
Volume
3
fYear
1999
fDate
1999
Firstpage
1725
Abstract
Efficient second order algorithm for training feedforward neural networks is presented. The algorithm has a similar convergence rate as the Lavenberg-Marquardt (LM) method and it is less computationally intensive and requires less memory. This is especially important for large neural networks where the LM algorithm becomes impractical. Algorithm was verified with several examples
Keywords
computational complexity; convergence; feedforward neural nets; learning (artificial intelligence); multilayer perceptrons; computational complexity; convergence rate; efficient second-order algorithm; feedforward neural network training; hidden neural layer; modified Lavenberg-Marquardt method; modified Levenberg-Marquardt method; Backpropagation algorithms; Convergence; Equations; Feedforward neural networks; Jacobian matrices; Neural networks; Neurons; Performance analysis; Stability; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.832636
Filename
832636
Link To Document