DocumentCode
1403500
Title
Existence, learning, and replication of periodic motions in recurrent neural networks
Author
Ruiz, A. ; Owens, David H. ; Townley, Stuart
Author_Institution
Centre for Syst. & Control Eng., Exeter Univ., UK
Volume
9
Issue
4
fYear
1998
fDate
7/1/1998 12:00:00 AM
Firstpage
651
Lastpage
661
Abstract
A class of recurrent neural networks is shown to possess a stable limit cycle. A gradient type algorithm is used to modify the parameters of the network so that it learns and replicates autonomously a time varying periodic signal. The results are applied to controlling the repetitive motion of a two-link robot manipulator
Keywords
learning (artificial intelligence); limit cycles; recurrent neural nets; stability; time-varying systems; gradient type algorithm; parameter modification; periodic motion learning; periodic motion replication; recurrent neural networks; repetitive motion; stable limit cycle; time varying periodic signal; two-link robot manipulator; Bifurcation; Control engineering; Intelligent networks; Learning systems; Limit-cycles; Manipulator dynamics; Motion control; Neural networks; Recurrent neural networks; Robots;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.701178
Filename
701178
Link To Document