- Referenced in 589 articles
- identification problem and a discretized optimal control problem, both of which are used to demonstrate ... method for the solution of nonlinear least squares problems. Both, overdetermined and underdetermined nonlinear least...
- Referenced in 510 articles
- solve linear equations and linear least-squares problems. The package solves linear systems whose matrices ... indefinite, symmetric positive definite, triangular, and tridiagonal square. In addition, the package computes ... rectangular matrices and applies them to least-squares problems. LINPACK uses column-oriented algorithms...
- Referenced in 394 articles
- solving systems of linear equations, least squares problems, and eigenvalue problems. The goals of both ... factorization, matrix inversion, full-rank linear least squares problems, orthogonal and generalized orthogonal factorizations, orthogonal...
- Referenced in 486 articles
- singular value decomposition to solve certain least-squares problems. EISPACK has been superseded...
- Referenced in 343 articles
- LSQR: Sparse Linear Equations and Least Squares Problems. An iterative method is given for solving...
- Referenced in 1582 articles
- linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value...
- Referenced in 152 articles
- norm solution of an underdetermined least-squares problem. Basis Pursuit DeNoise (BPDN) fits the least ... squares problem only approximately, and a single parameter determines a curve that traces the optimal ... trade-off between the least-squares fit and the one-norm of the solution ... gradient-projection method approximately minimizes a least-squares problem with an explicit one-norm constraint...
- Referenced in 208 articles
- total least squares problem: computational aspects and analysis. Total least squares...
- Referenced in 96 articles
- linear systems of equations and linear least squares problems, in particular for systems with multiple...
Harwell-Boeing sparse matrix collection
- Referenced in 208 articles
- test set comprises problems in linear systems, least squares, and eigenvalue calculations from a wide ... variety of scientific and engineering disciplines. The problems range from small matrices, used as counter...
- Referenced in 89 articles
- including systems of linear equations, linear least squares problems, eigenvalue problems, and singular value problems...
- Referenced in 59 articles
- LSMR: an iterative algorithm for sparse least-squares problems. An iterative method LSMR is presented ... solving linear systems Ax=b and least-squares problems min∥Ax-b∥ 2 , with...
- Referenced in 70 articles
- invert a matrix, to solve least squares problems, to perform unconstrained minimization, to compute eigenvalues...
- Referenced in 57 articles
- MATLAB solver for the l1-regularized least squares problem: A fast algorithm for sparse reconstruction...
- Referenced in 51 articles
- become a standard technique for nonlinear least-squares problems and can be thought...
- Referenced in 274 articles
- Solve linear, quadratic, integer, and nonlinear optimization problems. Optimization Toolbox™ provides functions for finding parameters ... quadratic programming, nonlinear optimization, and nonlinear least squares. You can use these solvers to find ... optimal solutions to continuous and discrete problems, perform tradeoff analyses, and incorporate optimization methods into...
- Referenced in 38 articles
- linear equations and large sparse least squares problems...
- Referenced in 29 articles
- LIBrary); a set of Matlab solvers, test problems, graphical and computational utilities for unconstrained ... quadratic programming, unconstrained and constrained nonlinear least squares, boxbounded global optimization, global mixed- integer nonlinear ... problems. Using MEXfile interfaces, problems in the CUTE test problem data base and problems defined ... algorithms are implemented for the nonlinear least squares problem to approxi mate sums of exponential...
- Referenced in 21 articles
- used to solve the nonlinear ordinary least squares problem. The procedure has application to curve ... procedure that exploits the structure of the problem so that the computational cost per iteration ... algorithm applied to the nonlinear ordinary least squares problem. The package allows a general weighting...
- Referenced in 28 articles
- systems of nonlinear equations and nonlinear least-squares problems using tensor methods. This article describes...