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Semidefinite and second-order cone optimization approach for the Toeplitz matrix approximation problem
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S. Al-Homidan
Published/Copyright:
March 1, 2006
The nearest positive semidefinite symmetric Toeplitz matrix to an arbitrary data covariance matrix is useful in many areas of engineering, including stochastic filtering and digital signal processing applications. In this paper, the interior point primal-dual path-following method will be used to solve our problem after reformulating it into different forms, first as a semidefinite programming problem, then into the form of a mixed semidefinite and second-order cone optimization problem. Numerical results, comparing the performance of these methods against the modified alternating projection method will be reported.
Key Words: primal-dual interior-point method,; projection method,; semidefinite programming,; Toeplitz matrix
Published Online: 2006-03-01
Published in Print: 2006-03-01
Copyright 2006, Walter de Gruyter
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Articles in the same Issue
- Semidefinite and second-order cone optimization approach for the Toeplitz matrix approximation problem
- Distributed optimal control of lambda–omega systems
- Local analysis of discontinuous Galerkin methods applied to singularly perturbed problems
- A posteriori error estimates for adaptive finite element discretizations of boundary control problems
Keywords for this article
primal-dual interior-point method,;
projection method,;
semidefinite programming,;
Toeplitz matrix
Articles in the same Issue
- Semidefinite and second-order cone optimization approach for the Toeplitz matrix approximation problem
- Distributed optimal control of lambda–omega systems
- Local analysis of discontinuous Galerkin methods applied to singularly perturbed problems
- A posteriori error estimates for adaptive finite element discretizations of boundary control problems
