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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.)

single level ,two level, multi level dwt for the denoising

基于小波变换的碰磨故障信号的特征提取，可以画出信号原图，轴心轨迹，频谱图以及多层小波变换的重构信号(Based on wavelet transform rubbing fault signal feature extraction, the signal can be drawn artwork, orbit, spectrum and signal reconstruction wavelet multi-)

小波分解在图像处理和电能质量分析中应用广泛，本文应用小波分解的方法将高频的暂态信号提取出来，获取暂态信号的特征量，就能够有效地计算暂态信号。(Wavelet decomposition in image processing and power quality analysis is widely used, this application of wavelet decomposition method to extract high-frequency transient signals, to obtain the amount of transient characteristics of the signal, we can effectively calculate the transient signal.)

对于非平稳信号，小波多尺度分解师一种有效的信号去噪方法，在小波去噪方法的基础上，提出了基于Lipschitz指数的小波阈值去噪方法(For non-stationary signals, signal de-noising of wavelet multi-scale decomposition ' is an effective method, wavelet denoising method based on proposed wavelet thresholding denoising method based on the Lipschitz exponent)

《MATAB小波分析（第2版）》张德丰 书籍配套所有源代码("MATAB wavelet analysis (Second Edition)" - Zhang Defeng, books supporting all the source code)

基于matlab的小波变换程序，可以方便的进行信号的小波分析。经过验证，可以使用。这里使用的是morlet小波。主要是处理地震数据。(Matlab-based wavelet transform process, you can easily carry out the wavelet analysis of signals. After verification, you can use. Here use morlet wavelet. Processing seismic data.)

基于小波变换的图像压缩感知 并且进行OMP重建 对压缩感知的性能与采样点数进行性能分析与比较(Image compression based on wavelet transform perception and the OMP reconstruction performance of compressed sensing and sample analysis and comparison of performance points)

本文研究的是利用奇异性指数实现对设备状态监视和故障预警功能。首先用LabVIEW 采集传感器电信号，然后对采集到的电信 号进行小波变换得到信号包络奇异点的奇异性指数，即设备运行状态的特征值(In this research project, we use LabVIEW to do wavelet-transformation to the signal collected by sensors in order to get singularity index from the singular points of the particular signal’s envelope. Through comparing this eigenvalue to the figures in a standard database, we can know the functional status of the instruments. Not only the diagnoses are continuously displayed, but alarms about signs of dysfunction will also be raised in a proper way. In other words, both the supervision of the instrument and warning of dysfunction can be achieved)

《小波十讲（修订版）》主要内容简介：原书《小波十讲》（ten lectures on wavelets）是一本世界范围公认的经典学术名著，是当代数学著作中一本影响巨大的绝妙好书。(text book for wavelet analysis)