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  2. Kalman filter - Wikipedia

    en.wikipedia.org/wiki/Kalman_filter

    The Kalman filter is an efficient recursive filter estimating the internal state of a linear dynamic system from a series of noisy measurements. It is used in a wide range of engineering and econometric applications from radar and computer vision to estimation of structural macroeconomic models, [ 25 ] [ 26 ] and is an important topic in ...

  3. Extended Kalman filter - Wikipedia

    en.wikipedia.org/wiki/Extended_Kalman_filter

    Extended Kalman filter. In estimation theory, the extended Kalman filter (EKF) is the nonlinear version of the Kalman filter which linearizes about an estimate of the current mean and covariance. In the case of well defined transition models, the EKF has been considered [1] the de facto standard in the theory of nonlinear state estimation ...

  4. Finite impulse response - Wikipedia

    en.wikipedia.org/wiki/Finite_impulse_response

    The impulse response (that is, the output in response to a Kronecker delta input) of an N th -order discrete-time FIR filter lasts exactly samples (from first nonzero element through last nonzero element) before it then settles to zero. FIR filters can be discrete-time or continuous-time, and digital or analog.

  5. Wiener filter - Wikipedia

    en.wikipedia.org/wiki/Wiener_filter

    The Wiener filter problem has solutions for three possible cases: one where a noncausal filter is acceptable (requiring an infinite amount of both past and future data), the case where a causal filter is desired (using an infinite amount of past data), and the finite impulse response (FIR) case where only input data is used (i.e. the result or ...

  6. Least mean squares filter - Wikipedia

    en.wikipedia.org/wiki/Least_mean_squares_filter

    The basic idea behind LMS filter is to approach the optimum filter weights (), by updating the filter weights in a manner to converge to the optimum filter weight. This is based on the gradient descent algorithm.

  7. Recursive least squares filter - Wikipedia

    en.wikipedia.org/wiki/Recursive_least_squares_filter

    Recursive least squares filter. Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This approach is in contrast to other algorithms such as the least mean squares (LMS) that aim to reduce the mean square ...

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