Name
Abstract | ||
|---|---|---|
In this paper, we consider the problem of quickly detecting an abrupt change in linear regression models. Specifically, an observer sequentially obtains a sequence of observations, whose underlying linear model changes at an unknown time. Moreover, the pre-change linear model is perfectly known by the observer but the post-change linear model is unknown. The observer aims to design an efficient on... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TSP.2019.2914893 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
Observers,Biological system modeling,Signal processing algorithms,Linear regression,Bayes methods,Change detection algorithms,Delays | Online algorithm,Mathematical optimization,Change detection,Linear model,Proper linear model,Bayesian multivariate linear regression,Observer (quantum physics),Linear predictor function,Mathematics,Linear regression | Conference |
Volume | Issue | ISSN |
67 | 12 | 1053-587X |
Citations | PageRank | References |
2 | 0.47 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Geng | 1 | 24 | 6.31 |
| Bingwen Zhang | 2 | 16 | 2.54 |
| Lauren M. Huie | 3 | 47 | 6.43 |
| Lifeng Lai | 4 | 2289 | 167.78 |