Name
Title | ||
|---|---|---|
Recursive Identification For Multivariate Autoregressive Equation-Error Systems With Autoregressive Noise |
Abstract | ||
|---|---|---|
This paper considers the recursive identification problems for a class of multivariate autoregressive equation-error systems with autoregressive noise. By decomposing the system into several regressive identification subsystems, a maximum likelihood recursive generalised least squares identification algorithm is proposed to identify the parameter vectors in each subsystem. In addition, a multivariate recursive generalised least squares algorithm is derived as a comparison. The numerical simulation results indicate that the maximum likelihood recursive generalised least squares algorithm can effectively estimate the parameters of the multivariate autoregressive equation-error autoregressive systems and get more accurate parameter estimates than the multivariate recursive generalised least squares algorithm. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1080/00207721.2018.1511873 | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE |
Keywords | Field | DocType |
Recursive identification, multivariate system, maximum likelihood, recursive least squares | Least squares,Applied mathematics,Autoregressive model,Mathematical optimization,Computer simulation,Multivariate statistics,Maximum likelihood,Least mean square algorithm,Recursive least squares filter,Recursion,Mathematics | Journal |
Volume | Issue | ISSN |
49 | 13 | 0020-7721 |
Citations | PageRank | References |
0 | 0.34 | 32 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lijuan Liu | 1 | 0 | 1.01 |
| Feng Ding | 2 | 4973 | 231.42 |
| Quanmin Zhu | 3 | 321 | 41.09 |