Denoising the wavelet periodogram using the Haar- Fisz transform
نویسندگان
چکیده
The wavelet periodogram is hard to smooth because of the low signal-to-noise ratio and non-stationary covariance structure. This article introduces a method for denoising a local wavelet periodogram by applying a Haar-Fisz transform which Gaussianises and stabilizes the variance of the periodogram. Consequently the transformed periodogram is easier to smooth. This article demonstrates the superiority of the new method over existing methods and supplies theory that proves the Gaussianising, variance stabilizing and decorrelation properties of the Haar-Fisz transform.
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