A successive projection method
Mathematical Programming: Series A and B
Sizing and least-change secant methods
SIAM Journal on Numerical Analysis
Iterative methods for solving linear systems
Iterative methods for solving linear systems
The Solution to a Structured Matrix Approximation Problem Using Grassman Coordinates
SIAM Journal on Matrix Analysis and Applications
NEOS and Condor: solving optimization problems over the Internet
ACM Transactions on Mathematical Software (TOMS)
LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
ACM Transactions on Mathematical Software (TOMS)
Finite element solution of boundary value problems: theory and computation
Finite element solution of boundary value problems: theory and computation
On the Nesterov--Todd Direction in Semidefinite Programming
SIAM Journal on Optimization
The role of abstract algebra in structured estimation theory
IEEE Transactions on Information Theory
An H infinity (H∞) design scheme for an air blown gasification cycle unit using matlab
ICOSSE'06 Proceedings of the 5th WSEAS international conference on System science and simulation in engineering
| Hi-index | 7.29 |
Positive semidefinite Hankel matrices arise in many important applications. Some of their properties may be lost due to rounding or truncation errors incurred during evaluation. The problem is to find the nearest matrix to a given matrix to retrieve these properties. The problem is converted into a semidefinite programming problem as well as a problem comprising a semidefined program and second-order cone problem. The duality and optimality conditions are obtained and the primal-dual algorithm is outlined. Explicit expressions for a diagonal preconditioned and crossover criteria have been presented. Computational results are presented. A possibility for further improvement is indicated.