wd.object {wavethresh} | R Documentation |
These are objects of class "wd" They represent a decomposition of a function with respect to a wavelet basis.
To retain your sanity the C and D coefficients should be extracted
by the accessC
and accessD
functions and put using
the putC
and putD
functions, rather than
by the $
operator.
Mind you, if you want to muck about with coefficients directly,
then you'll have to do it yourself by working out what the fl.dbase
list means.
wd
object.
C |
a vector containing each level's smoothed data.
The wavelet transform works by applying both a smoothing filter
and a bandpass filter to the previous level's smoothed data,
the top level containing data at the highest resolution level.
This the ``pyramid structure of Mallat''.
Each of these levels are stored one after the other in this vector.
The matrix fl.dbase$first.last.c determines exactly where each
level is stored in the vector.Usually, accessC should be used to extract C
components.
|
D |
wavelet coefficients. If you were to write down the discrete
wavelet transform of a function, then these D would be the
coefficients of the wavelet basis functions. Like the C, they are
also formed in a pyramidal manner, but stored in a linear array.
The storage details are to be found in fl.dbase$first.last.d .Usually, accessD should be used to extract D
components.
|
nlevels |
The number of resolution levels in the pyramidal decomposition that produces
the coefficients. Therefore, 2^nlevels = 2^m is the
number of data points used in the decomposition.
This means there will be m levels of wavelet coefficients (indexed
0,1,2,..., m-1), and m+1 levels of smoothed data
(indexed 0,1,2,...{},m).
|
fl.dbase |
The first/last database associated with this decomposition.
This is a list consisting of 2 integers, and 2 matrices. The matrices
detail how the coefficients are stored in the C and D components
of the wd.object .
In the decomposition `extra' coefficients are generated that help take
care of the boundary effects, this database lists where these start and
finish, so the "true" data can be extracted.
See |
filter |
a list containing the details of the filter that did the decomposition |
bc |
how the boundaries were handled |
This class of objects is returned from the wd
function
to represent a wavelet decomposition of a function.
Other functions also return a wd.object
The "wd"
class of objects has methods for the following generic
functions:
plot
, threshold
, summary
, print
, draw
.
Release 2.2 Copyright Guy Nason 1993
wd
for examples and background.