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Kalman filter

The Kalman filter (named after its inventor, Rudolf Kalman) is an efficient recursive computational solution for tracking a time-dependent state vector with noisy equations of motion in real time by the least-squares method. It is used to separate signal from noise so as to optimally predict changes in a modeled system with time.

Kalman filtering is used extensively in control systems engineering.

Compare with: Wiener filter

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