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stat.ME2026
Machine Learning Integrated in Wavelet Shrinkage (MLShrink)
Dixon Vimalajeewa, Vijini Lakmini, Brani Vidakovic
Data encountered in practice are frequently contaminated by additive noise, and wavelet shrinkage remains a fundamental tool for recovering underlying signals in nonparametric esti…
stat.ME2026
SCOPE Shrinkage: A Unified Framework for Wavelet Denoising
Dixon Vimalajeewa, Vijini Lakmini, Malith Premarathna +2
We introduce Symmetric CDF Oriented Probability Enhanced (SCOPE) shrinkage, a unified family of sign-preserving shrinkage rules constructed from centered cumulative distribution fu…
stat.ME2025
The Dual Wavelet Spectra: An Alternative Perspective on Hurst Exponent Estimation with Application to Mammogram Classification
Raymond J. Hinton, Pepa RamÃrez Cobo, Brani Vidakovic
The wavelet spectra is a common starting point for estimating the Hurst exponent of a self-similar signal using wavelet-based techniques. The decay of the average energy o…