Determine an Orthonormal Basis for the Discrete Wavelet Packet
确定一个标准正交基的离散小波包
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Subroutine for use in simulating seasonal persistent processes using the discrete wavelet packet transform.
用于模拟季节性的进程中,采用离散小波包变换的子程序。
用法----------Usage----------
参数----------Arguments----------
参数:wf
Character string; name of the wavelet filter.
字符串的小波过滤器的名称。
参数:J
Depth of the discrete wavelet packet transform.
深度的离散小波包变换。
参数:fG
Gegenbauer frequency.
盖根堡的频率。
参数:eps
Threshold for the squared gain function.
阈值的平方增益功能。
Details
详细信息----------Details----------
The squared gain functions for a Daubechies (extremal phase or least asymmetric) wavelet family are used in a filter cascade to compute the value of the squared gain function for the wavelet packet filter at the Gengenbauer frequency. This is done for all nodes of the wavelet packet table.
的平方的增益函数为Daubechies小波(的极值相或至少非对称)小波族中使用的滤波器的级联,小波包滤波器在Gengenbauer频率的平方的增益函数来计算的值。这样做是为了所有节点的小波包表。
The idea behind this subroutine is to approximate the relationship between the discrete wavelet transform and long-memory processes, where the squared gain function is zero at frequency zero for all levels of the DWT.
该子程序背后的想法是近似的离散小波变换和术语记忆的过程,其中的平方增益功能是零频零的DWT各级之间的关系。
值----------Value----------
Boolean vector describing the orthonormal basis for the DWPT.
布尔向量描述的正交的DWPT基础的。