DocumentCode
2705411
Title
Application of GRG2 for training neural networks
Author
Subramanian, Venkat ; Hung, Ming S.
Author_Institution
Wisconsin Univ., Kenosha, WI, USA
fYear
1991
fDate
8-14 Jul 1991
Firstpage
207
Abstract
The authors present a new training system based on GRG2, a widely distributed nonlinear optimization software. Comparisons with backpropagation based upon three benchmark problems suggest not only that the GRG2-based system is much faster, robust, and offers solutions with better quality, but that it also offers better scalability to larger problems
Keywords
computer aided instruction; distributed processing; learning systems; mathematics computing; neural nets; nonlinear programming; GRG2; Generalised Reduced Gradient; backpropagation; distributed nonlinear optimization software; encoding; neural networks; nonlinear programming; scalability; training system; Artificial neural networks; Convergence; Design optimization; Feedforward systems; Least squares approximation; Neural networks; Robustness; Scalability; Software algorithms; Spirals;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155339
Filename
155339
Link To Document