Name
Title | ||
|---|---|---|
Two-Stage Multi-Innovation Stochastic Gradient Algorithm For Multivariate Output-Error Arma Systems Based On The Auxiliary Model |
Abstract | ||
|---|---|---|
This paper investigates the parameter estimation problem for multivariate output-error systems perturbed by autoregressive moving average noises. Since the identification model has two different kinds of parameters, a vector and a matrix, the gradient algorithm cannot be used directly. Therefore, we decompose the original system model into two sub-models and proceed the identification problem by the collaboration between the two sub-models. By employing the gradient search and determining the optimal step-sizes, we present an auxiliary model based two-stage projection algorithm. However, in order to alleviate the sensitivity to the noise, we reselect the step-sizes and derive the auxiliary model based two-stage stochastic gradient (AM-2S-SG) algorithm. Based on the AM-2S-SG algorithm, an auxiliary model based two-stage multi-innovation stochastic gradient algorithm is proposed to generate more accurate estimates. Finally, numerical simulations are provided to demonstrate the effectiveness of the proposed algorithms. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1080/00207721.2019.1690720 | INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE |
Keywords | Field | DocType |
Decomposition technique, stochastic gradient, multi-model collaboration, parameter estimation, multivariate system | Mathematical optimization,Multivariate statistics,Mathematics | Journal |
Volume | Issue | ISSN |
50 | 15 | 0020-7721 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qinyao Liu | 1 | 8 | 2.82 |
| Feng Ding | 2 | 4973 | 231.42 |
| Quanmin Zhu | 3 | 321 | 41.09 |
| Tasawar Hayat | 4 | 0 | 1.01 |