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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