Back to Search
Start Over
Data filtering based forgetting factor stochastic gradient algorithm for Hammerstein systems with saturation and preload nonlinearities.
- Source :
-
Journal of the Franklin Institute . Nov2016, Vol. 353 Issue 16, p4280-4299. 20p. - Publication Year :
- 2016
-
Abstract
- This paper considers the parameter estimation problem for Hammerstein systems with saturation and preload nonlinearities. Based on the key term separation technique, the output of the system is expressed as a linear combination of all the system parameters. By introducing the forgetting factors and using the data filtering technique, a data filtering based forgetting factor stochastic gradient (F-FF-SG) algorithm is presented. The simulation examples illustrate that the F-FF-SG algorithm has faster convergence rates and better parameter estimation accuracies than the stochastic gradient algorithm and the data filtering based stochastic gradient algorithm. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00160032
- Volume :
- 353
- Issue :
- 16
- Database :
- Academic Search Index
- Journal :
- Journal of the Franklin Institute
- Publication Type :
- Periodical
- Accession number :
- 118028555
- Full Text :
- https://doi.org/10.1016/j.jfranklin.2016.07.025