DocumentCode
2707687
Title
The autoregressive backpropagation algorithm
Author
Leighton, Russell R. ; Conrath, Bartley C.
Author_Institution
Mitre Corp., McLean, VA, USA
fYear
1991
fDate
8-14 Jul 1991
Firstpage
369
Abstract
Describes an extension to error backpropagation that allows the nodes in a neural network to encode state information in an autoregressive `memory´. This neural model gives such networks the ability to learn to recognize sequences and context-sensitive patterns. Building upon the work of A. Wieland (1990) concerning nodes with a single feedback connection, the authors generalize the method to n feedback connections and address stability issues. The learning algorithm is derived, and a few applications are presented
Keywords
feedback; learning systems; neural nets; pattern recognition; stability; autoregressive backpropagation algorithm; context-sensitive patterns; feedback connections; learning algorithm; neural network; sequence recognition; stability; state information encoding; Backpropagation algorithms; Context modeling; Delay; Difference equations; Digital filters; Neural networks; Neurofeedback; Neurons; Output feedback; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155362
Filename
155362
Link To Document