We consider the Georgiou-Lindquist constrained approximation of spectra in the Kullback-Leibler sense. We propose an alternative iterative algorithm to solve the corresponding convex optimization problem. The Lagrange multiplier is computed as a fixed point of a nonlinear matricial map. Simulation indicates that the algorithm is extremely effective.
On the Georgiou-Lindquist approach to constrained Kullback-Leibler approximation of spectral densities
PAVON, MICHELE;FERRANTE, AUGUSTO
2006
Abstract
We consider the Georgiou-Lindquist constrained approximation of spectra in the Kullback-Leibler sense. We propose an alternative iterative algorithm to solve the corresponding convex optimization problem. The Lagrange multiplier is computed as a fixed point of a nonlinear matricial map. Simulation indicates that the algorithm is extremely effective.
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