scholarly journals Least-squares algorithms for finding solutions of overdetermined systems of linear equations which minimize error in a smooth strictly convex norm

1973 ◽  
Vol 8 (1) ◽  
pp. 46-61 ◽  
Author(s):  
V.P Sreedharan
Keyword(s):  
Least Squares ◽  
Linear Equations ◽  
Strictly Convex ◽  
Overdetermined Systems ◽  
Strictly Convex Norm ◽  
Systems Of Linear Equations ◽  
Convex Norm

A Nonlinear Least-Squares Graphical Tool (‘Gaussfit’) for Educational Purposes

2010 ◽  
Vol 47 (1) ◽  
pp. 11-22 ◽  
Author(s):  
Krešimir Malarić ◽  
Roman Malarić ◽  
Hrvoje Hegeduš
Keyword(s):  
Least Squares ◽  
Input Data ◽  
Least Squares Method ◽  
Linear Equations ◽  
Computer Calculation ◽  
Nonlinear Least Squares ◽  
Undergraduate Level ◽  
Graphical Tool ◽  
Systems Of Linear Equations ◽  
Graphical Presentation

This paper describes a computer program that finds a function which closely approximates experimental data using the least-squares method. The program finds parameters of the function as well as their corresponding uncertainties. It also has a subroutine for graphical presentation of the input data and the function. The program is used for educational purposes at undergraduate level for students who are learning least-squares fitting, how to solve systems of linear equations and about computer calculation errors.

scholarly journals Modified Preconditioned GAOR Methods for Systems of Linear Equations

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Xue-Feng Zhang ◽  
Qun-Fa Cui ◽  
Shi-Liang Wu
Keyword(s):  
Linear System ◽  
Convergence Rate ◽  
Least Squares ◽  
Linear Equations ◽  
Generalized Least Squares ◽  
Numerical Results ◽  
Least Squares Problem ◽  
Comparison Results ◽  
Systems Of Linear Equations ◽  
Better Than

Three kinds of preconditioners are proposed to accelerate the generalized AOR (GAOR) method for the linear system from the generalized least squares problem. The convergence and comparison results are obtained. The comparison results show that the convergence rate of the preconditioned generalized AOR (PGAOR) methods is better than that of the original GAOR methods. Finally, some numerical results are reported to confirm the validity of the proposed methods.

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