DocumentCode
3313720
Title
Backpropagation through time for a general class of recurrent network
Author
De Jeses, O. ; Hagan, Martin T.
Author_Institution
Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK, USA
Volume
4
fYear
2001
fDate
2001
Firstpage
2638
Abstract
This paper introduces a general class of dynamic network, the layered digital dynamic network. It then derives the backpropagation-through-time algorithm for computing the gradient of the network error with respect to the weights of the network
Keywords
backpropagation; multilayer perceptrons; recurrent neural nets; backpropagation-through-time algorithm; layered digital dynamic network; network error gradient; network weights; recurrent neural network; Backpropagation algorithms; Computer architecture; Computer errors; Computer networks; Equations; Feedback loop; Neural networks; Neurofeedback; Output feedback; Perturbation methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-7044-9
Type
conf
DOI
10.1109/IJCNN.2001.938786
Filename
938786
Link To Document