Title :
Backpropagation algorithm for a generalized neural network structure
Author :
KrishnaKumar, K.
Author_Institution :
Dept. of Aerosp. Eng., Alabama Univ., Tuscaloosa, AL, USA
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;
Conference_Titel :
Southeastcon '92, Proceedings., IEEE
Conference_Location :
Birmingham, AL
Print_ISBN :
0-7803-0494-2
DOI :
10.1109/SECON.1992.202276
