Name
Title | ||
|---|---|---|
A Data-Based Augmented Model Identification Method for Linear Errors-in-Variables Systems Based on EM Algorithm. |
Abstract | ||
|---|---|---|
With a large amount of industrial data available, it is of considerable interest to develop data-based models. The challenge lies in the significant noises that appear in all data collected from industry. The errors-in-variables (EIV) model is a model that accounts for measurement noises in all observations (both input and output). In most of the traditional EIV identification methods, the input g... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TIE.2017.2703680 | IEEE Transactions on Industrial Electronics |
Keywords | Field | DocType |
Maximum likelihood estimation,Heuristic algorithms,Parameter estimation,Computational modeling,Classification algorithms | Errors-in-variables models,Control theory,Computer science,Process dynamics,Input/output,Artificial intelligence,Estimation theory,System identification,Kalman smoother,Expectation–maximization algorithm,Algorithm,Statistical classification,Machine learning | Journal |
Volume | Issue | ISSN |
64 | 11 | 0278-0046 |
Citations | PageRank | References |
1 | 0.36 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fan Guo | 1 | 12 | 5.25 |
| Ouyang Wu | 2 | 2 | 1.39 |
| Yongsheng Ding | 3 | 976 | 95.80 |
| Biao Huang | 4 | 746 | 120.96 |