KALMAN FILTER
##article.abstract##
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.
##submission.citations##
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