title: Decimative spectral estimation with unconstrained model order.
abstract: This paper presents a new state-space method for spectral estimation that performs decimation by any factor, it makes use of the full set of data and brings further apart the poles under consideration, while imposing almost no constraints to the size of the Hankel matrix (model order), as decimation increases. It is compared against two previously proposed techniques for spectral estimation (along with derived decimative versions), that lie among the most promising methods in the field of spectroscopy, where accuracy of parameter estimation is of utmost importance. Moreover, it is compared against a state-of-the-art purely decimative method proposed in literature. Experiments performed on simulated NMR signals prove the new method to be more robust, especially for low signal-to-noise ratio.
authors.affiliation: Department of Voice and Sound Technology, Institute for Language and Speech Processing / "Athena" R.C., Maroussi, Paradissos Amaroussiou, Greece.
authors.forename: Stavroula-Evita
authors.initials: SE
authors.lastname: Fotinea
authors.forename: Ioannis
authors.initials: I
authors.lastname: Dologlou
authors.forename: Stylianos
authors.initials: S
authors.lastname: Bakamidis
authors.forename: Theologos
authors.initials: T
authors.lastname: Athanaselis
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008962:Models, Theoretical; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio