A globally convergent matricial algorithm for multivariate spectral estimation

2008/09/29 by Federico Ramponi, Ramponi, Federico, Augusto Ferrante +3
Computer Science · Engineering · Mathematics · #Advanced Adaptive Filtering Techniques #Blind Source Separation Techniques #Control Systems and Identification #FOS: Mathematics #Optimization and Control (math.OC) #math.OC

paper · pdf · doi:10.48550/arxiv.0809.5024

arxiv created 2008/09/29 · openalex publication_date 2008/09/29 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

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