منابع مشابه
Kernel Recursive Least Squares
We present a non-linear kernel-based version of the Recursive Least Squares (RLS) algorithm. Our Kernel-RLS algorithm performs linear regression in the feature space induced by a Mercer kernel, and can therefore be used to recursively construct the minimum meansquared-error regressor. Sparsity (and therefore regularization) of the solution is achieved by an explicit greedy sparsification proces...
متن کاملRecursive 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 کاملApproximate QR-Based Algorithms for Recursive Nonlinear Least Squares Estiamtion
This paper proposes new approximate QR-based algorithms for recursive nonlinear least squares (NLS) estimation. Two QR decomposition-based recursive algorithms are introduced based on the classical Gauss-Newton (GN) and Levenberg-Marquardt (LM) algorithms in nonlinear unconstrained optimization or least squares problems. Instead of using the matrix inversion formula, recursive QR decomposition ...
متن کاملError propagation properties of recursive least-squares adaptation algorithms
-The numerical properties of implementations of the cessing/systolic arrays and/or VLSI chiprecursive least-squares identification algorithm are of grea t implementation. importance for their continuous use in various adaptive schemes. Here we investigate how an error that is introduced at an (d) Programming investment required. arbitrary point in the algorithm propagates. It is shown that (e) ...
متن کاملAlgorithms and Architectures for Split Recursive Least Squares
In this paper, a new computationally efficient algorithm for recursive least-squares (RLS) filtering is presented. The proposed Split RLS algorithm can perform the approximated RLS with O ( N ) complexity for signals having no special data structure t o be exploited. Our performance analysis shows that the estimation bias will be small when the input data are less correlated. We also show that ...
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 Vehicular Technology
سال: 2016
ISSN: 0018-9545,1939-9359
DOI: 10.1109/tvt.2016.2533664