iterative least-squares algorithms
Finite Iterative Algorithm for Solving a Class of Complex Matrix Equation with Two Unknowns of General Form
... gradient iterative algorithms for general matrix equations [6, 12] and hierarchical least squares iterative algorithms for generalized coupled Sylvester matrix equations and ...
12
Least squares-based iterative identification methods for linear-in-parameters systems using the decomposition technique
... the least squares based iterative (LSI) method, this paper presents a decom- position based LSI (D-LSI) algorithm for identifying linear-in-parameters systems and an interval- varying D-LSI algorithm ...
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Title: Multicarrier Iterative Generalized Least Squares Data Extraction in Digital Images
... BSS algorithms are not effective in the presence of correlated signal interference as is the case in SS multimedia embedding and degrade rapidly as the dimension of the carrier (signature) decreases relative to ...
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High performance numerical algorithms and software for structured total least squares
... Shortly after the publication of the work on the CTLS problem, De Moor lists many applications of the STLS problem and outlines a new framework for deriving analytical properties and numerical methods [7]. His approach ...
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Least Squares Solutions of Generalized Sylvester Equation with Xi Satisfies Different Linear Constraint
... solutions. Iterative algorithms have been received much attention to solve linear matrix equations in recent ...derived iterative solutions of matrix equations AXB = F and generalized Sylvester ...
16
A predictor corrector iterative method for solving linear least squares problems and perturbation error analysis
... The method in (1.14) performs 5 Mms. Recently several systematic algorithms for fac- torizations of the hyperpower iterative family (1.9) of arbitrary orders have been given in [17] for computing outer ...
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Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares
... Sketching algorithms were applied to the JAFFE face expression using a sketch dimension of M = 100 for the classical sketch, and N = 5 iterations with m = 20 sketches per iteration for the IHS ...
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Identification of nonlinear systems with non-persistent excitation using an iterative forward orthogonal least squares regression algorithm
... 2 The problems caused by non-persistent excitation can be solved by experiment design. Optimal input design for nonlinear system identification has been studied (Hjalmarsson and Martensson, 2007, Larsson et al., 2010, ...
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Data filtering-based least squares iterative algorithm for Hammerstein nonlinear systems by using the model decomposition
... three-stage least squares iterative identification algorithm for output error moving average systems using the model decomposition [21]; Bai and Liu presented a normalized iterative method to ...
17
Stabilized Least Squares Migration
... migration algorithms are designed to find the adjoint of the solution to the wave equation rather than its ...“least squares migration”. Least squares migration (LSM) is an attempt to ...
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Distributed Learning with Regularized Least Squares
... approximate algorithms have been introduced in the literature such as low-rank approximations of ker- nel matrices for kernel principal component analysis (Sch¨ olkopf et ...of iterative optimization ...
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Two modified least squares iterative algorithms for the Lyapunov matrix equations
... From the three curves in Fig. 1, we find that: (1) iterative scheme (2.2)–(2.4) with μ = 1 is divergent, while iterative scheme (2.2)–(2.4) with μ = 0.99, 0.2 is convergent; (2) the constant 1 maybe the ...
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Iterative least squares method for global positioning system
... The presented method is very efficient for the implemen- tation of the standard triangulation method based on non- linear LS. In future work we apply this idea to recursive com- putations of the position estimates using ...
6
08_Linear_Classification_2.pdf
... University Probabilistic Generative Models Continuous Input Discrete Features Probabilistic Discriminative Models Logistic Regression Iterative Reweighted Least Squares Laplace Approxima[r] ...
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Hierarchical Generalized Linear Models: The R Package HGLMMM
... First of all, to our knowledge prior to this R package the h-likelihood algorithms were im- plemented only in GenStat (Payne, Murray, Harding, Baird, and Soutar 2009) software. The capabilities of HGLMMM and ...
20
Image magnification by least squares surfaces
... In this paper, a new method of the least squares surface has been used to enlarge images. Despite simple implementation and low computational com- plexity, this method provides more satisfactory results ...
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Likelihood estimation of the extremal index
... For the period 1772–1980 both the intervals and the iterative least squares methods suggested the possibility of a constant extremal index with a value slightly below 0.5. For the local linear ...
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RLScore: Regularized Least-Squares Learners
... RLScore implements a large variety of fast holdout and CV algorithms. A fast leave- group-out (LGO) CV (Pahikkala et al., 2012b), where folds containing multiple instances are left out, is provided, complementing ...
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Floating point error analysis of recursive least squares and least means squares adaptive filters
... This sequence is a zero mean white independent random process which has a variance related to signal statistics, the weight vector covariance, and the floating point errorso The calculat[r] ...
27
Off -Grid Direction-of-Arrival Estimation Using a Sparse Array Covariance Matrix
... alternating iterative algorithm that utilizes the alternating update of a convex optimization problem and a least-squares (LS) problem is presented to solve for the two sparse vectors in the modified ...
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