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Details for article 16 of 30 found articles
| Title: |
Off-line estimation of dynamic systems parameters in the presence of outliers in autoregressive noise |
| Author: |
Pupeikis, Rimantas |
| Appeared in: |
Informatica |
| Paging: | Volume 4 (2014) nr. 1-2 pages 94-110 |
| Year: |
2014-09-24 |
| Contents: |
In the previous paper (Pupeikis, 1992) the problem of off-line estimation of dynamic systems parameters in the presence of outliers in observations have been considered, when the filter generating an additive noise has a very special form. The aim of the given paper is the development, in such a case, of classical generalized least squares method (GLSM) algorithms for off-line estimation of unknown parameters of dynamic systems. Two approaches using batch processing of the stored data are worked out. The first approach is based on the application of S-, H-, W- algorithms used for calculation of M-estimates, and the second one rests on the replacement of the corresponding values of the sample covariance and cross-covariance functions by their robust analogues in respective matrices of GLSM and on a further application of the least squares (LS) parameter estimation algorithms. The results of numerical simulation by IBM PC/AT (Table 1) are given. |
| Publisher: |
IOS Press |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 16 of 30 found articles
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