ДИФУЗНА ІНІЦІАЛІЗАЦІЯ ФІЛЬТРА КАЛМАНА
The behavior of Kalman filter is studied at interpretation of unknown initial conditions as the random variables having a covariance matrix proportional to large positive parameter. The developed approach permits to express characteristics of the filter in an analytic form, to explain phenomenon of...
Збережено в:
| Дата: | 2011 |
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| Автор: | |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
V.M. Glushkov Institute of Cybernetics of NAS of Ukraine
2011
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| Онлайн доступ: | https://jais.net.ua/index.php/files/article/view/555 |
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| Назва журналу: | Problems of Control and Informatics |
Репозитарії
Problems of Control and Informatics| Резюме: | The behavior of Kalman filter is studied at interpretation of unknown initial conditions as the random variables having a covariance matrix proportional to large positive parameter. The developed approach permits to express characteristics of the filter in an analytic form, to explain phenomenon of divergence and suggest a limiting estimation algorithm which is independent of large initial parameter leading to divergence. As the application two problems — filtering with a sliding window and parameter estimation of separable regression are considered. The re-ceived results are illustrated by example of radial basic neural network training. |
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