К содержанию
РецензированоEN2025

KALMAN FILTER

Shokirov Shodmon Shoyimovich

Педагоги · 214-216 · 2025

Аннотация

In modern engineering and data science, especially within robotics, control systems, and sensor fusion, accurate state estimation is critical. Real-world measurements are inherently noisy, and dynamic systems often behave unpredictably. The Kalman Filter, developed by Rudolf E. Kálmán in 1960, provides an efficient computational solution to the problem of estimating the state of a system from noisy observations. It is widely celebrated for its predictive power, robustness, and computational efficiency.

Доказательный фрагмент

«In modern engineering and data science, especially within robotics, control systems, and sensor fusion, accurate state estimation is critical.»

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Демо-превью

In modern engineering and data science, especially within robotics, control systems, and sensor fusion, accurate state estimation is critical. Полный текст публикации CiteX не хранит — доступ к первоисточнику открывается по DOI согласно лицензии издателя и выбранному плану.

DOI не указан
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Тип
Журнал
Страна
Узбекистан
Ключевые слова
systems, state, noisy, computational
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