SOLVING REGULARIZED TOTAL LEAST SQUARES PROBLEMS BASED ON EIGENPROBLEMS
نویسندگان
چکیده
منابع مشابه
Solving Regularized Total Least Squares Problems Based on Eigenproblems
The total least squares (TLS) method is a successful approach for linear problems if both the system matrix and the right hand side are contaminated by some noise. For ill-posed TLS problems regularization is necessary to stabilize the computed solution. In this paper we summarize two iterative methods which are based on a sequence of eigenproblems. The focus is on efficient implementation with...
متن کاملA Fast Algorithm for Solving Regularized Total Least Squares Problems
The total least squares (TLS) method is a successful approach for linear problems if both the system matrix and the right hand side are contaminated by some noise. For ill-posed TLS problems Renaut and Guo [SIAM J. Matrix Anal. Appl., 26 (2005), pp. 457 476] suggested an iterative method which is based on a sequence of linear eigenvalue problems. Here we analyze this method carefully, and we ac...
متن کاملRegularized Total Least Squares Based on Quadratic Eigenvalue Problem Solvers
This paper presents a new computational approach for solving the Regularized Total Least Squares problem. The problem is formulated by adding a quadratic constraint to the Total Least Square minimization problem. Starting from the fact that a quadratically constrained Least Squares problem can be solved via a quadratic eigenvalue problem, an iterative procedure for solving the regularized Total...
متن کاملRegularized total least squares approach for nonconvolutional linear inverse problems
In this correspondence, a solution is developed for the regularized total least squares (RTLS) estimate in linear inverse problems where the linear operator is nonconvolutional. Our approach is based on a Rayleigh quotient (RQ) formulation of the TLS problem, and we accomplish regularization by modifying the RQ function to enforce a smooth solution. A conjugate gradient algorithm is used to min...
متن کاملA Regularized Total Least Squares Algorithm
Error-contaminated systems Ax ≈ b, for which A is ill-conditioned, are considered. Such systems may be solved using Tikhonov-like regularized total least squares (R-TLS) methods. Golub et al, 1999, presented a direct algorithm for the solution of the Lagrange multiplier formulation for the R-TLS problem. Here we present a parameter independent algorithm for the approximate R-TLS solution. The a...
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: Taiwanese Journal of Mathematics
سال: 2010
ISSN: 1027-5487
DOI: 10.11650/twjm/1500405873