5 citations · 6 across the 10 of their papers we have counts for
3 papers · 1 filter
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…
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…
Gamma-Minimax Wavelet Shrinkage with Three-Point Priors
Dixon Vimalajeewa, Brani Vidakovic
In this paper we propose a method for wavelet denoising of signals contaminated with Gaussian noise when prior information about the -energy of the signal is available. Assumi…