Algorithms for adaptive estimation of dynamic objects under the influence of additive noise
| dc.contributor.author | Zaripova, Shaxlo | |
| dc.date.accessioned | 2025-10-29T09:31:14Z | |
| dc.date.available | 2025-10-29T09:31:14Z | |
| dc.date.issued | 2024-09-11 | |
| dc.description | The Kalman filter is widely used in numerous tasks of synthesizing and designing systems for managing dynamic objects of various functional purposes [1-9]. The Kalman filter provides an unbiased estimate with minimal variance about the state of a discrete linearly varying dynamic system, the input and output of which are distorted by Gaussian white noise with an additive character. This approach was extended to continuous dynamical systems by Kalman and Bucy with a linear character | en_US |
| dc.description.abstract | Algorithms for adaptive evaluation of dynamic object control systems under the influence of additive noise are considered. Algorithms of the Kalman filter are given. An adaptive filtering approach for nonlinear systems with additive noise is also considered. The developed adaptive estimation algorithm can calculate the square root of the covariance matrix in a simple way in such a way that positive semi-certainty is guaranteed, which significantly increases the stability and accuracy of the filter. | en_US |
| dc.identifier.isbn | 978-625-99572-2-7 | |
| dc.identifier.uri | https://dspace.kstu.uz/xmlui/handle/123456789/1071 | |
| dc.language.iso | en_US | en_US |
| dc.subject | Adaptive filtering, Kalman filter, Nonlinear systems | en_US |
| dc.title | Algorithms for adaptive estimation of dynamic objects under the influence of additive noise | en_US |
| dc.title.alternative | 4th International Conference on Research of Agricultural and Food Technologies | en_US |
| dc.type | Article | en_US |