Description: 这是小波包程序，好不容易从网上下的，希望对大家有用！-This is the wavelet packet procedures, under the hard-line, in the hope that useful! Platform: |
Size: 640000 |
Author:xiao li |
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Description: 2-band discrete wavelet transform (DWT)
Dual-Tree Complex Wavelet Packet-The 2-band discrete wavelet transform (DWT) provides
an octave-band analysis in the frequency domain, but this
might not be ‘optimal’ for a given signal. The discrete wavelet
packet transform (DWPT) provides a dictionary of bases over
which one can search for an optimal representation (without
constraining the analysis to an octave-band one) for the signal
at hand. However, it is well known that both the DWT and the
DWPT are shift-varying. Also, when these transforms are extended
to 2-D and higher dimensions using tensor products, they
do not provide a geometrically oriented analysis. The dual-tree
complex wavelet transform (DT-CWT), introduced by Kingsbury,
is approximately shift-invariant and provides directional analysis
in 2-D and higher dimensions. In this paper, we propose a method
to implement a dual-tree complex wavelet packet transform (DTCWPT),
extending the DT-CWT as the DWPT extends the DWT.
To find the best complex wavelet packet frame for a given
signal, w Platform: |
Size: 4096 |
Author:王方 |
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Description: 基于小波包的带通滤波器设计程序。给出了小波变换的快速算法和重构算法，讨论了应用小波变换进行信号带通滤波的方法，并通过正交小波包对信号的分解，把频率成分复杂的信号分解到各个频带上，根据需要提取指定频率的信号，然后用小波包重构算法对信号进行重构，实现对信号的提取。-Based on wavelet packet band-pass filter design program. Given the fast algorithm of wavelet transform and reconstruction algorithms are discussed using wavelet transform signal band-pass filtering method, and through the wavelet packet to signals can be decomposed, 把 frequency components of complex signal is decomposed into various frequency bands 上, according to need to extract the specified frequency signal, and then reconstructs the signal reconstruction algorithm to achieve the extraction of the signal. Platform: |
Size: 1024 |
Author:王综新 |
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Description: 首先将非平稳的故障振动信号进行双树复小波包分解，得
到不同频带的分量；然后对每个分量求其峭度值和相关系数并进行比较；最后选取峭度值和相关系数较大的分量
进行软阈值降噪和双树复小波包重构，即可有效地消除振动信号中噪声的干扰，同时保留信号中的有效信息即实
现了故障特征信息的提取。-In view of the above situation, a new fault diagnosis
method is proposed based on dual-tree complex wavelet packet transform and threshold de-noising. Firstly, the
non-stationary fault signal is decomposed into several different frequency band components through dual-tree
complex wavelet packet decomposition. Secondly, Kurtosis and the cross-correlation coefficient of each
component are obtained and compared. Due to the kurtosis reflecting the signal variations, if the kurtosis value is
bigger, the degree of the change of signal is bigger too. The correlation coefficient can reflect the proximity
between the component and the original signal at the same time, the correlation coefficient is bigger, the more
similar with the original signal. Finally, the components that have a bigger value are chosen to be de-noised by a
soft threshold and reconstructed by dual-tree complex wavelet packet transform. The noise interference was
eliminated effectively, and the effective si Platform: |
Size: 1164288 |
Author:侯蒙蒙 |
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Description: 首先根据高斯白噪声频率充满整个频带的特性，通过双树复小波包变换对高斯白噪声进行分解，利用频带能量泄漏的定量分析方法，验证了双树复小波包变换具有较低的频带能量泄漏特性；其次利用双树复小波包变换逐层分解信号，对每层分解所得分量求其FFT谱的峭度，得到基于双树复小波包变换的谱峭度图，根据图中峭度最大的原则，可以自动准确的选择信号分解最佳层数和最佳分量；最后将基于双树复小波包变换的谱峭度图的故障诊断方法应用于实际工程中，对齿轮故障振动信号进行分析，选择最佳分解层数和分量后利用希尔伯特包络解调，有效准确地提取了故障特征信息，验证了方法的可行性和有效性-The parameters of a filter were determined by experience, and that has a great influence on the
results of signal processing. The discrete wavelet packet transform has a larger energy leakage of frequency band,
which obviously affected the results of the envelope demodulation. It is necessary to have a method with a lower
energy leakage of the frequency band before envelope demodulation. The dual tree complex wavelet packet
transform (DT-CWPT) was a new signal processing method that had many good qualities. Because the energy
leakage of the frequency band was smaller when the signal was decomposed by a dual tree complex wavelet
packet transform, the dual tree complex wavelet packet transform was used to extract the fault feature information
in the field of fault diagnosis. In this paper, first, according to the characteristics of Gaussian white noise, whose
frequency was full of the whole frequency band, Gaussian white noise was decomposed by a dual-tree complex
wavel Platform: |
Size: 401408 |
Author:侯蒙蒙 |
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Search - complex wavelet packet transform