Title :
An extension of the back-propagation algorithm to three dimensions by vector product
Author_Institution :
Electrotech. Lab., Ibaraki, Japan
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;
Conference_Titel :
Tools with Artificial Intelligence, 1993. TAI '93. Proceedings., Fifth International Conference on
Conference_Location :
Boston, MA
Print_ISBN :
0-8186-4200-9
DOI :
10.1109/TAI.1993.634002
