9 citations · 43 across the 33 of their papers we have counts for
13 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…
The Dual Wavelet Spectra: An Alternative Perspective on Hurst Exponent Estimation with Application to Mammogram Classification
Raymond J. Hinton, Pepa Ramírez 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…
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…
Robust Wavelet-based Assessment of Scaling with Applications
Erin K. Hamilton, Seonghye Jeon, Pepa Ramirez Cobo +2
A number of approaches have dealt with statistical assessment of self-similarity, and many of those are based on multiscale concepts. Most rely on certain distributional assumption…
Non-decimated 2D Wavelet Spectrum and Its Use in Breast Cancer Diagnostics
Minkyoung Kang, William Auffermann, Brani Vidakovic
To improve diagnostic accuracy of breast cancer detection, several researchers have used the wavelet-based tools, which provide additional insight and information for aiding diagno…
Wavelet-based estimation of power densities of size-biased data
Michel H. Montoril, Aluísio Pinheiro, Brani Vidakovic
We propose a new wavelet-based method for density estimation when the data are size-biased. More specifically, we consider a power of the density of interest, where this power exce…
Bayesian Wavelet Shrinkage with Beta Priors
Alex Rodrigo dos Santos Sousa, Nancy Lopes Garcia, Branislav Vidakovic
In wavelet shrinkage and thresholding, most of the standard techniques do not consider information that wavelet coefficients might be bounded, although information about bounded en…
Least Squares Wavelet-based Estimation for Additive Regression Models using Non Equally-Spaced Designs
German A. Schnaidt Grez, Brani Vidakovic
Additive regression models are actively researched in the statistical field because of their usefulness in the analysis of responses determined by non-linear relationships with mul…
Bayesian nonparametric regression using complex wavelets
Norbert Reményi, Brani Vidakovic
In this paper we propose a new adaptive wavelet denoising methodology using complex wavelets. The method is based on a fully Bayesian hierarchical model in the complex wavelet doma…
Estimation of the Hurst Exponent Using Trimean Estimators on Nondecimated Wavelet Coefficients
Chen Feng, Brani Vidakovic
Hurst exponent is an important feature summarizing the noisy high-frequency data when the inherent scaling pattern cannot be described by standard statistical models. In this paper…
MEDL and MEDLA: Methods for Assessment of Scaling by Medians of Log-Squared Nondecimated Wavelet Coefficients
Minkyoung Kang, Brani Vidakovic
High-frequency measurements and images acquired from various sources in the real world often possess a degree of self-similarity and inherent regular scaling. When data look like a…
A note on Bayesian wavelet-based estimation of scaling
Minkyoung Kang, Brani Vidakovic
A number of phenomena in various fields such as geology, atmospheric sciences, economics, to list a few, can be modeled as a fractional Brownian motion indexed by Hurst exponent $H…