IEEE Transactions on Automatic Control, Vol.53, No.4, 954-967, 2008
Hellinger versus Kullback-Leibler multivariable spectrum approximation
In this paper, we study a matricial version of a generalized moment problem with degree constraint. We introduce a new metric on multivariable spectral densities induced by the family of their spectral factors, which, in the scalar case, reduces to the Hellinger distance. We solve the corresponding constrained optimization problem via duality theory. A highly nontrivial existence theorem for the dual problem is established in the Byrnes-Lindquist spirit. A matricial Newton-type algorithm is finally provided for the numerical solution of the dual problem. Simulation indicates that the algorithm performs effectively and reliably.
Keywords:approximation of multivariable power spectra;convex optimization;Hellinger distance;Kullback-Leibler index;matricial descent method