CNLTreg-package: Complex-Valued Wavelet Lifting for Signal Denoising

Description Details Author(s) References See Also

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

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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


CNLTreg documentation built on May 2, 2019, 12:21 p.m.