nd.dwt(x, wavelet="s8", n.levels=6, dual=F,
analysis.filter=NULL, synthesis.filter=NULL,
filter.reverse=F)
"d4", "s8",
see
wavelet for all available wavelet names.
For user-provided filter, input the values in
analysis.filter below.
n.levels is bigger than
ml, where
ml is the maximum possible level,
then
n.levels is set to
ml and a warning message is given.
The
max.level function is used to compute
ml.
wavelet for details.
filter argument in
wave.filter for
details.
filter argument in
wave.filter for
details. When
analysis.filter is provided, then the default
synthesis.filter
is also
analysis.filter.
nd.dwt, inheriting from the classes
dwt
,
wpt,
wp and
crystal.vector.
or an object of class
nd.dwt.list, inheriting from the classes
dwt.list
,
wpt.list,
wp.list and
crystal.list.
See
crystal.vector.object and
crystal.list.object for details.
The non-decimated discrete wavelet transform is non-orthogonal
variant to the classical DWT.
With the non-decimated DWT, starting with
n sample values,
you end up with
(J+1) n coefficients.
Unlike the classical DWT,
which has fewer coefficients at coarse scales,
each scale for the non-decimated DWT has
n coefficients.
The non-decimated wavelet
transform can be inverted using the
reconstruct function.
Refer to the section "Non-Decimated Wavelets" in the
S+WAVELETS User's Manual
for more details about the
nd.dwt function.
All the default optional arguments can be reset using function
wavelet.options
. See
wavelet.options for details.
Signal
x is assumed to be periodic. Other boundary rules are not available
for
nd.dwt.
Mallat, S. and Hwang, W. L. (1992). Singularity Detection and Processing with Wavelets. IEEE Transactions on Information Theory, 38 (2), 617-643. Shensa, M. J. (1992). The Discrete Wavelet Transform: Wedding the A Trous and Mallat Algorithms. IEEE Transactions on Signal Processing, 40 (10), 2464-2482.
xx <- make.signal("doppler")
nd <- nd.dwt(xx, n.levels=4)
eda.plot(nd)