DocumentCode
3066688
Title
Backpropagation algorithm for a generalized neural network structure
Author
KrishnaKumar, K.
Author_Institution
Dept. of Aerosp. Eng., Alabama Univ., Tuscaloosa, AL, USA
fYear
1992
fDate
12-15 Apr 1992
Firstpage
646
Abstract
The author presents a generalized neural network structure and the associated backpropagation learning algorithm. This structure is an extension of a neural net structure presented by P.J. Werbos (1988, 1990). Generalization is aimed at ease of implementation and flexibility in structure selection. It is shown how certain network structures can be accommodated using this general structural form. Networks that are investigated include feedforward, recurrent, and memory networks
Keywords
backpropagation; feedforward neural nets; recurrent neural nets; self-organising feature maps; backpropagation learning algorithm; feedforward; generalized neural network structure; memory networks; recurrent; Backpropagation algorithms; Computer networks; Electronic mail; Joining processes; Neural networks; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Southeastcon '92, Proceedings., IEEE
Conference_Location
Birmingham, AL
Print_ISBN
0-7803-0494-2
Type
conf
DOI
10.1109/SECON.1992.202276
Filename
202276
Link To Document