Name
Title | ||
|---|---|---|
A modified iteratively reweighted correlation analysis algorithm for robust parameter estimation of output error systems with colored heavy-tailed noises |
Abstract | ||
|---|---|---|
In many areas of engineering, the distribution of the measurements always departs from Gaussian to be heavy-tailed due to the presence of outliers, and most of the traditional identification algorithms such as the gradient based and the least-squares based algorithms are not robust in that case. This paper proposes a modified iteratively reweighted correlation analysis algorithm for robust parameter estimation of output error systems with colored heavy-tailed noises. The proposed algorithm is adopted to get the robust finite impulse response auxiliary model, and with the reconstructed noise-free output, the parameters of the output error system can be easily identified by a least squares method. The basic idea of the modified algorithm is to replace the t-distribution based m-estimator with the Tukey's biweight m-estimator, so that the outliers in a specific region can be completely rejected. Compare to the original algorithm, the modified algorithm can achieve higher estimation accuracy in Gaussian mixture noise, simulation results confirm this conclusion. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.23919/IConAC.2017.8082039 | 2017 23rd International Conference on Automation and Computing (ICAC) |
Keywords | Field | DocType |
parameter estimation,output error system,heavy-tailed noise,iterative,m-estimator | Least squares,M-estimator,Colored,Outlier,Algorithm,Gaussian,Estimation theory,Finite impulse response,Mathematics,Correlation analysis | Conference |
ISBN | Citations | PageRank |
978-1-5090-5040-6 | 0 | 0.34 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qibing Jin | 1 | 19 | 11.28 |
| Yunfei Xing | 2 | 0 | 0.34 |
| Beiyan Jiang | 3 | 1 | 0.70 |
| Xinghan Du | 4 | 1 | 0.70 |