Publications and Preprints
Estimation of parameters of two-dimensional sinusoidal signal in heavy-tailed errors
In this paper, we consider a two-dimensional sinusoidal model observed in a additive random field. The proposed model has wide applications
signal processing. The additive noise has mean zero but the variance may not be finite. We propose the least squares estimators to
estimate the unknown parameters. It is observed that the least squares estimators are strongly consistent. We obtain the asymptotic
distribution of the least squares estimators under the assumption that the additive errors are from a symmetric stable distribution.
Some numerical experiments are performed to see how the results work for finite samples.
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