mfilter.select(wavethresh)
mfilter.select()所属R语言包：wavethresh
Provide filter coefficients for multiple wavelets.
提供多个小波滤波器系数。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function returns the filter coefficients necessary for doing a discrete multiple wavelet transform (and its inverse).
这个函数返回的滤波器系数需要做一个离散多小波变换（和它的逆）。
用法----------Usage----------
mfilter.select(type = "Geronimo")
参数----------Arguments----------
参数：type
The name for the multiple wavelet basis. The two possible types are "Geronimo" and "Donovan3".
名称为多个小波基。的两个可能的类型是“Geronimo的”和“Donovan3”的。
Details
详细信息----------Details----------
This function supplies the multiple wavelet filter coefficients required by the mwd function.
此功能提供了多种小波滤波器系数的mwd功能。
A multiple wavelet filter is somewhat different from a single wavelet filter. Firstly the filters are made up of matrices not single coefficients. Secondly there is no simple expression for the high pass coefficients G in terms of the low pass coefficients H, so both sets of coefficients must be specified. Note also that the transpose of the filter coefficients are used in the inverse transform, an unnecessary detail with scalar coefficients. There are two filters available at the moment. Geronimo is the default, and is recommended as it has been checked thoroughly. Donovan3 uses three orthogonal wavelets described in Donovan et al. but this coding has had little testing.
从一个单一的小波滤波器的多小波滤波器是有所不同的。首先，过滤器是由的矩阵不是单一系数。其次有没有简单的表达方面的低通系数H为高通系数G，所以必须指定两套系数。还请注意，转置中使用的滤波器系数的逆变换，与标量系数的一个不必要的细节。有两个过滤器，可在那一刻。 Geronimo是默认情况下，推荐，因为它已经彻底检查。 donovan3使用在Donovan等人所描述的三个正交小波。但这个编码有小的测试。
See Donovan, Geronimo and Hardin, 1996 and Geronimo, Hardin and Massopust, 1994.
见多诺万Geronimo和哈丁，1996年和Geronimo，哈丁和Massopust，1994年。
This function fulfils the same purpose as the filter.select function does for the standard DWT wd.
此功能实现相同的的目的filter.select功能不标准DWT wd。
值----------Value----------
A list is returned with the following eight components which describe the filter:
以下八个部分组成，描述了过滤器返回一个列表：
<table summary="R valueblock"> <tr valign="top"><td>type</td> <td> The multiple wavelet basis type string.</td></tr> <tr valign="top"><td>H</td> <td> A vector containing the low pass filter coefficients.</td></tr> <tr valign="top"><td>G</td> <td> A vector containing the high pass pass filter coefficients.</td></tr> <tr valign="top"><td>name</td> <td> A character string containing the full name of the filter.</td></tr> <tr valign="top"><td>nphi</td> <td> The number of scaling functions in the multiple wavelet basis.</td></tr> <tr valign="top"><td>npsi</td> <td> The number of wavelet functions in the multiple wavelet basis.</td></tr> <tr valign="top"><td>NH</td> <td> The number of matrix coefficients in the filter. This is different from length(H).</td></tr> <tr valign="top"><td>ndecim</td> <td> The decimation factor. I.e. the scale ratio between two successive resolution levels.</td></tr> </table>
<table summary="R valueblock"> <tr valign="top"> <TD>type </ TD> <TD>多个小波基类型的字符串。</ TD> </ TR> <TR VALIGN =“”> <TD>H </ TD> <td>一个向量的低通滤波器系数。</ TD> </ TR> <tr valign="top"> <TD> X> </ TD> <TD>一个向量，包含高通低通滤波器的系数。</ TD> </ TR> <tr valign="top"> <TD>G </ TD> <TD一个字符串包含完整的过滤器的名称。</ TD> </ TR> <tr valign="top"> <TD>name </ TD> <TD>的缩放功能多小波的基础。</ TD> </ TR> <tr valign="top"> <TD>nphi </ TD> <TD>在多个小波基的小波函数的数量。</ TD> </ TR> <tr valign="top"> <TD>npsi</ TD> <TD>在过滤器中的矩阵系数。这是不同长度（H）</ TD> </ TR> <tr valign="top"> <TD>NH </ TD> <TD>的抽取因子。即两个连续的分辨率级别的规模之间的比例。</ TD> </ TR> </ TABLE>
RELEASE----------RELEASE----------
Version 3.9.6 (Although Copyright Tim Downie 1995-6)
版本3.9.6（虽然版权蒂姆·唐尼1995-96）
（作者）----------Author(s)----------
Tim Downie
参见----------See Also----------
accessC.mwd, accessD.mwd, draw.mwd, mfirst.last, mwd.object, mwd, mwr, plot.mwd, print.mwd, putC.mwd, putD.mwd, summary.mwd, threshold.mwd, wd, wr.mwd.
accessC.mwd，accessD.mwd，draw.mwd，mfirst.last，mwd.object，mwd，mwr，plot.mwd，print.mwd，putC.mwd，putD.mwd，summary.mwd，threshold.mwd，wd，wr.mwd。
实例----------Examples----------
#This function is currently used by `mwr' and `mwd' in decomposing and[此功能目前使用的分解和水利部“和MWD]
#reconstructing, however you can view the coefficients.[重建，但是你可以查看系数。]
#[]
# look at the filter coefficients for Geronimo multiwavelet[看Geronimo的多小波滤波器系数为]
#[]
mfilter.select()
#$type:[$类型：]
#[1] "Geronimo"[[1]“的Geronimo”]
#[]
#$name:[$名称：]
#[1] "Geronimo Multiwavelets"[[1]“Geronimo的多小波”]
#[]
#$nphi:[$ nphi：]
#[1] 2[[1] 2]
#[]
#$npsi:[$ NPSI：]
#[1] 2[[1] 2]
#[]
#$NH:[$ NH：]
#[1] 4[[1] 4]
#[]
#$ndecim:[$ ndecim：]
#[1] 2[[1] 2]
#$H:[$ H：]
# [1] 0.4242641 0.8000000 -0.0500000 -0.2121320 0.4242641 0.0000000[[1] 0.4242641 0.8000000 -0.0500000 -0.2121320 0.4242641 0.0000000]
# [7] 0.4500000 0.7071068 0.0000000 0.0000000 0.4500000 -0.2121320[[7] 0.4500000 0.7071068 0.0000000 0.0000000 0.4500000 -0.2121320]
#[13] 0.0000000 0.0000000 -0.0500000 0.0000000[[13] 0.0000000 0.0000000 -0.0500000 0.0000000]
#[]
#$G:[$ G：]
# [1] -0.05000000 -0.21213203 0.07071068 0.30000000 0.45000000 -0.70710678[[1] -0.05000000 -0.21213203 0.07071068 0.30000000 0.45000000 -0.70710678]
#[]
# [7] -0.63639610 0.00000000 0.45000000 -0.21213203 0.63639610 -0.30000000[[7] -0.63639610 0.00000000 0.45000000 -0.21213203 0.63639610 -0.30000000]
#[13] -0.05000000 0.00000000 -0.07071068 0.00000000[[13] -0.05000000 0.00000000 -0.07071068 0.00000000]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 17:26:35
