CNLTreg-package {CNLTreg}R Documentation

Complex-Valued Wavelet Lifting for Signal Denoising

Description

Implementations of recent complex-valued wavelet shrinkage procedures for smoothing irregularly sampled signals, see Hamilton et al (2018) <doi:10.1080/00401706.2017.1281846>.

Details

The DESCRIPTION file:

Package: CNLTreg
Type: Package
Title: Complex-Valued Wavelet Lifting for Signal Denoising
Version: 0.1-2
Date: 2018-07-18
Author: Matt Nunes [aut, cre], Marina Knight [aut], Jean Hamilton [ctb], Piotr Fryzlewicz [ctb]
Authors@R: c(person("Matt","Nunes", role=c("aut","cre"),email="nunesrpackages@gmail.com"),person("Marina", "Knight", role="aut"), person("Jean", "Hamilton", role="ctb"), person("Piotr", "Fryzlewicz", role="ctb"))
Maintainer: Matt Nunes <nunesrpackages@gmail.com>
Description: Implementations of recent complex-valued wavelet shrinkage procedures for smoothing irregularly sampled signals, see Hamilton et al (2018) <doi:10.1080/00401706.2017.1281846>.
License: GPL-2
Depends: adlift, miscTools, nlt
Suggests: MASS

Index of help topics:

CNLTreg-package         Complex-Valued Wavelet Lifting for Signal
                        Denoising
cnlt.reg                Performs 'nondecimated' complex-valued wavelet
                        lifting for signal denoising
denoisepermC            Denoises a signal using the complex-valued
                        lifting transform and multivariate soft
                        thresholding
denoisepermCh           Denoises a signal using the complex-valued
                        lifting transform and multivariate soft
                        thresholding and heteroscedastic variance
                        computation
fwtnppermC              Forward complex wavelet lifting transform
mthreshC                Function to perform 'multiwavelet style'
                        level-dependent soft thresholding for
                        complex-valued wavelet coefficients
orthpredfilters         Computes orthogonal filters

The main routines of the package are denoisepermC and cnlt.reg which perform complex-valued lifting-based denoising, using a single or a multiple (chosen) number of lifting trajectories, respectively.

Author(s)

Matt Nunes [aut, cre], Marina Knight [aut], Jean Hamilton [ctb], Piotr Fryzlewicz [ctb]

Maintainer: Matt Nunes <nunesrpackages@gmail.com>

References

Hamilton, J., Nunes, M. A, Knight, M. I. and Fryzlewicz, P. (2018) Complex-valued wavelet lifting and applications. Technometrics, 60 (1), 48-60, DOI 10.1080/00401706.2017.1281846.

For related literature on the lifting methodology adopted in the technique, see

Nunes, M. A., Knight, M. I and Nason, G. P. (2006) Adaptive lifting for nonparametric regression. Stat. Comput. 16 (2), 143–159.

Knight, M. I. and Nason, G. P. (2009) A 'nondecimated' wavelet transform. Stat. Comput. 19 (1), 1–16.

See Also

denoise denoiseperm nlt


[Package CNLTreg version 0.1-2 Index]