SQP algorithms for solving Toeplitz matrix approximation problem
Copyright policy )SQP algorithms for solving Toeplitz matrix approximation problem
AbstractGiven an n × n matrix F, we find the nearest symmetric positive semi‐definite Toeplitz matrix T to F. The problem is formulated as a non‐linear minimization problem with positive semi‐definite Toeplitz matrix as constraints. Then a computational framework is given. An algorithm with rapid convergence is obtained by l1 Sequential Quadratic Programming (SQP) method. Copyright © 2002 John Wiley & Sons, Ltd.
- King Fahd University of Petroleum and Minerals Saudi Arabia
Methods of successive quadratic programming type, Applications of mathematical programming, filter SQP, Numerical mathematical programming methods, \(l_1\) SQP method, Toeplitz matrix, non-smooth optimization, positive semi-definite matrix
Methods of successive quadratic programming type, Applications of mathematical programming, filter SQP, Numerical mathematical programming methods, \(l_1\) SQP method, Toeplitz matrix, non-smooth optimization, positive semi-definite matrix
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