dwpt(waveslim)
dwpt()所属R语言包：waveslim
(Inverse) Discrete Wavelet Packet Transforms
（反）离散小波包变换
译者：生物统计家园网 机器人LoveR
描述----------Description----------
All possible filtering combinations (low- and high-pass) are performed to decompose a vector or time series. The resulting coefficients are associated with a binary tree structure corresponding to a partitioning of the frequency axis.
所有可能的过滤组合（低通和高通）进行分解的向量或时间序列。将所得的系数与对应于在频率轴中的分区的二进制树结构。
用法----------Usage----------
idwpt(y, y.basis)
modwpt(x, wf = "la8", n.levels = 4, boundary = "periodic")
参数----------Arguments----------
参数：x
a vector or time series containing the data be to decomposed. This must be a dyadic length vector (power of 2).
的向量或包含数据的时间序列分解。这必须是一个二元的长度矢量（2的幂）。
参数：wf
Name of the wavelet filter to use in the decomposition. By default this is set to "la8", the Daubechies orthonormal compactly supported wavelet of length L=8 (Daubechies, 1992), least asymmetric family.
的小波滤波器的名称使用在分解。默认情况下，此设置为"la8"的Daubechies正交的紧支撑小波的长度L=8（Daubechies小，1992年），至少不对称的家庭。
参数：n.levels
Specifies the depth of the decomposition. This must be a number less than or equal to log2[length(x)].
指定的深度的分解。这必须是一个小于或等于log2[length(x)]。
参数：boundary
Character string specifying the boundary condition. If boundary=="periodic" the default, then the vector you decompose is assumed to be periodic on its defined interval,<br> if boundary=="reflection", the vector beyond its boundaries is assumed to be a symmetric reflection of itself.
字符串指定的边界条件。如果boundary=="periodic"默认值，则假定矢量分解其定义的时间间隔上是周期性的，<br>请如果boundary=="reflection"，超出其边界的矢量假定是一个对称反射本身。
参数：y
Object of S3 class dwpt.
对象的S3类dwpt。
参数：y.basis
Vector of character strings that describe leaves on the DWPT basis tree.
矢量字符的字符串描述上的DWPT的基础树的叶。
Details
详细信息----------Details----------
The code implements the one-dimensional DWPT using the pyramid algorithm (Mallat, 1989).
该代码实现的一维DWPT，使用金字塔算法（Mallat的，1989年）。
值----------Value----------
Basically, a list with the following components
基本上，与以下组件的列表
参数：w?.?
Wavelet coefficient vectors. The first index is associated with the scale of the decomposition while the second is associated with the frequency partition within that level.
小波系数向量。的第一个索引与规模的分解，而第二个是与该水平内的频率分区。
参数：wavelet
Name of the wavelet filter used.
小波滤波器的名称。
参数：boundary
How the boundaries were handled.
的界限如何处理。
（作者）----------Author(s)----------
B. Whitcher
参考文献----------References----------
A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 11, No. 7, 674-693.
Wavelet Methods for Time Series Analysis, Cambridge University Press.
Adapted Wavelet Analysis from Theory to Software, A K Peters.
参见----------See Also----------
dwt, modwpt, wave.filter.
dwt，modwpt，wave.filter。
实例----------Examples----------
data(mexm)
J <- 4
mexm.mra <- mra(log(mexm), "mb8", J, "modwt", "reflection")
mexm.nomean <- ts(
apply(matrix(unlist(mexm.mra), ncol=J+1, byrow=FALSE)[,-(J+1)], 1, sum),
start=1957, freq=12)
mexm.dwpt <- dwpt(mexm.nomean[-c(1:4)], "mb8", 7, "reflection")
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。
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发表于 2012-10-1 17:03:33
