iwt: Inverse discrete wavelet transform

In FRESHD: Fast Robust Estimation of Signals in Heterogeneous Data

Inverse discrete wavelet transform

Description

This function performs a level J decomposition of the input array (1d, 2d, or 3d) using the pyramid algorithm (Mallat 1989).

Usage

iwt(x, wf = "la8", J = NULL)

Arguments

x	a 1, 2, or 3 dimensional data array. The size of each dimension must be dyadic.
wf	the type of wavelet family used. See R-package waveslim for options.
J	is the level (depth) of the decomposition. For default NULL the max depth is used making iwt(x) equal to multiplying x with the inverse of corresponding wavelet matrix.

Details

This is a C++/R wrapper function for a C implementation of the inverse discrete wavelet transform by Brandon Whitcher licensed under the BSD 3 license https://cran.r-project.org/web/licenses/BSD_3_clause, see the Waveslim package; Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001).

Given a data array (1d, 2d or 3d) with dyadic dimensions sizes this transform is computed efficiently via the pyramid algorithm see Mallat (1989).

Value

...	An array with dimensions equal to those of x.

Author(s)

Adam Lund, Brandon Whitcher

References

Gencay, R., F. Selcuk and B. Whitcher (2001) An Introduction to Wavelets and Other Filtering Methods in Finance and Economics, Academic Press.

Mallat, S. G. (1989) A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 11, No. 7, 674-693.

Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.

Examples

###1d
x <- as.matrix(rnorm(2^3))
range(x - iwt(wt(x)))

###2d
x <- matrix(rnorm(2^(3 + 4)), 2^3, 2^4)
range(x - iwt(wt(x)))

###3d
x <- array(rnorm(2^(3 + 4 + 5)), c(2^3, 2^4, 2^5))
range(x - iwt(wt(x)))

FRESHD documentation built on May 12, 2022, 9:06 a.m.