| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4976460 | Journal of the Franklin Institute | 2010 | 12 Pages |
Abstract
The performance of the residual-based extended stochastic gradient (ESG) algorithms for identifying CARMA models with disturbances is analyzed under weaker conditions on statistical properties of the noise. The paper derives the conditions under which the parameter estimation errors converge to zero. Three examples are given to show the advantages of the proposed algorithm.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Yongsong Xiao, Dongqing Wang, Feng Ding,