Wavelet-analysis

一个基于小波阈值的信号处理程序，通过自适应阈值方式抑制信号噪声(A threshold based on wavelet signal processing procedures, through the adaptive threshold signal noise suppression methods)

1.实现非抽样提升小波包三层分解 2.有效解决了小波包分解频带交错问题 3.有效输出频谱图(1 non-sampling improved wavelet packet three decomposition. Effective solution to the wavelet packet decomposition band interlacing problems. Effective output spectrogram)

说明：  小波阈值去噪，用于对以为信号降噪处理，代码为matlab代码，亲测有效(Wavelet threshold denoising)

说明：  提出了一种基于复解析小波变换的相位诊断齿轮故障的方法。复解析小波变换将Hilbert变换与小波分析紧密结合在一起,具有自适应分析能力。利用复解析小波变换得到齿轮振动信号的相位,其功率谱图上可提取调制边频带结构来识别故障模式。试验结果表明这种方法可有效应用于齿轮局部故障诊断中。(A new method using the phase based on complex analytical wavelet transform for fault diagnosis of gears was proposed. The phase of vibration signals of gears is got by complex analytical wavelet transform, which combines Hilbert transform with wavelet transform tightly and possesses adaptive analysis ability. By making spectrum analysis of the phase, the sideband structure in power spectrum can be protruded, and the fault pattern can be identified. Experimental results show that the proposed method is effective in local defect detection of gears.)

对仿真信号进行复morlet小波变换后，绘制的时频图。(After the simulated signal multiplexing morlet wavelet transform, time-frequency diagram drawn.)

java小波变换的实现，包括哈尔小波，以及在这基础上改进的小波实现。(The implementation of Daubechies wavelets.)

小波包分析提取振动信号中的分解，系数重构特征频率，以及能量谱分析计算(Wavelet packet analysis to extract the vibration signal decomposition coefficient reconstruction of the characteristic frequency, and calculate the energy spectrum analysis)

利用小波变换，通过设置阈值对图像进行去噪。 首先对图像用小波进行2层分解，然后通过设置硬阈值和软阈值的方法，对图像高频部分去噪。(The wavelet transform is used to denoise the image by setting threshold. Firstly, the image is decomposed into 2 layers by wavelet, and then the high frequency part of the image is denoised by setting the hard threshold and the soft threshold.)

说明：  提出了一种结合SVD的小波变换方法，对其在外弹道测量数据中的野值剔除进行了研究。对观测数据进行小波分解，将小波分解后的近似分量和细节分量组合实现相空间重构，作为SVD方法的输入观测矩阵，根据奇异 熵增量准则，对奇异值进行筛选，根据SVD逆变换重构原信号。这一方法克服了Hankel矩阵相空间构建方法数据 端点失真问题。以小波分解后分量重构的相空间可以满足正交性，进一步提高了SVD进行数据降噪和野值检测的精度。仿真数据和试验数据处理结果证明了这一方法的有效性。(Proposed a method of combining the SVD wavelet transform its outer ballistic measurement data in excluding outliers were studied. Observational data on wavelet decomposition, wavelet decomposition of the approximate combined component and detail component to achieve the phase space reconstruction, as the input observation matrix SVD method, based on singular entropy increment standards, singular value filter, according to the inverse transform heavy SVD structure of the original signal. This approach overcomes the Hankel matrix phase space construction method data endpoint distortion. Wavelet decomposition component of reconstruction phase space satisfy orthogonality, to further improve the SVD for data noise reduction and outlier detection accuracy. Simulation data and experimental data processing results prove the effectiveness of this approach.)

使用小波包变换分析信号的MATLAB程序, 使用小波包变换分析两个信号的特征向量和各频率成分的功率谱，很完整的一个应用程序 (Signal using wavelet packet analysis of MATLAB program, using wavelet packet analysis of two signal eigenvectors and the power spectrum of each frequency component, an application is complete)