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)