Markov and recursive least squares methods for the estimation of data with discontinuities
نویسندگان
چکیده
منابع مشابه
Recursive Least Squares Estimation
We start with estimation of a constant based on several noisy measurements. Suppose we have a resistor but do not know its resistance. So we measure it several times using a cheap (and noisy) multimeter. How do we come up with a good estimate of the resistance based on these noisy measurements? More formally, suppose x = (x1, x2, . . . , xn) T is a constant but unknown vector, and y = (y1, y2, ...
متن کاملRecursive Least-Squares Estimation in Case of Interval Observation Data
In the engineering sciences, observation uncertainty often consists of two main types: random variability due to uncontrollable external effects, and imprecision due to remaining systematic errors in the data. Interval mathematics is well-suited to treat this second type of uncertainty in, e. g., intervalmathematical extensions of the least-squares estimation procedure if the set-theoretical ov...
متن کاملRecursive Least-Squares Estimation for Systems with Unknown Inputs
This paper addresses the optimal filtering problem for systems with unknown inputs from the viewpoint of recursive least-squares estimation. The solution to the least-squares problem yields filter equations in information form. The relation between these filter equations and existing results is discussed. Finally, by establishing duality relations to the Kalman filter equations, a square-root i...
متن کاملDecomposition Methods for Least Squares Parameter Estimation
In this paper least squares method with matrix decomposition is revisited and a multiple model formulation is proposed The proposed formulation takes advantage of the well established decomposition methods but possesses a multiple model structure which leads to simpler and more exible implementations and produces more infor mation than the original least squares methods Several application exam...
متن کاملRecursive Generalized Total Least Squares with Noise Covariance Estimation
We propose a recursive generalized total least-squares (RGTLS) estimator that is used in parallel with a noise covariance estimator (NCE) to solve the errors-in-variables problem for multi-input-single-output linear systems with unknown noise covariance matrix. Simulation experiments show that the suggested RGTLS with NCE procedure outperforms the common recursive least squares (RLS) and recurs...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Acoustics, Speech, and Signal Processing
سال: 1990
ISSN: 0096-3518
DOI: 10.1109/29.103098