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Nandi, Swagata; Kundu, Debasis

Analyzing non-stationary signals using generalized multiple fundamental frequency model. (English) Zbl 1103.62084

J. Stat. Plann. Inference 136, No. 11, 3871-3903 (2006).
Summary: We propose a new generalized multiple frequency model to analyze non-stationary signals. The model under the assumption of additive stationary errors can be used quite effectively to analyze different signals. We propose the usual least-squares estimators to estimate the unknown parameters and it is shown that the estimators are strongly consistent. We obtain the asymptotic distributions also. The performance of the proposed model is compared with the multiple frequency model using Monte Carlo simulations. Finally, several real data are analyzed using both the proposed model and the multiple frequency model.

Cited in 6 Documents

MSC:

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62F12 Asymptotic properties of parametric estimators
94A12 Signal theory (characterization, reconstruction, filtering, etc.)
62B10 Statistical aspects of information-theoretic topics
62E20 Asymptotic distribution theory in statistics
65C05 Monte Carlo methods

Keywords:

multiple fundamental frequencies; sinusoidal model; asymptotic distribution
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References:

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