A Globally Convergent Matricial Algorithm for Multivariate Spectral Estimation

In this paper, we first describe a
matricial
Newton-type algorithm designed to solve the multivariable spectrum approximation problem. We then prove its
global
convergence. Finally, we apply this approximation procedure to
multivariate spectral estimation
, and test its effectiveness through simulation. Simulation shows that, in the case of
short observation records
, this method may provide a valid alternative to standard multivariable identification techniques such as Matlab's PEM and Matlab's N4SID.