DocumentCode
1964245
Title
An extension of the back-propagation algorithm to three dimensions by vector product
Author
Nitta, Tohru
Author_Institution
Electrotech. Lab., Ibaraki, Japan
fYear
1993
fDate
8-11 Nov 1993
Firstpage
460
Lastpage
461
Abstract
A 3D vector version of the backpropagation algorithm is proposed for multilayered neural networks in which a vector product operation is performed, and whose weights, threshold values, input and output signals are all 3D real numbered vectors. This new algortihm can be used to learn patterns considered of 3D vectors in a natural way. A 3D example was used to successfully test the new formulation
Keywords
backpropagation; feedforward neural nets; multilayer perceptrons; vectors; 3D vectors; backpropagation algorithm; input signals; multilayered neural networks; output signals; pattern learning; threshold values; vector product; weights; Cities and towns; Computer networks; Joining processes; Laboratories; Multi-layer neural network; Neural networks; Neurons; Petroleum; Quaternions; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 1993. TAI '93. Proceedings., Fifth International Conference on
Conference_Location
Boston, MA
ISSN
1063-6730
Print_ISBN
0-8186-4200-9
Type
conf
DOI
10.1109/TAI.1993.634002
Filename
634002
Link To Document