dtcwt_toolbox4_3

故障行波波头识别：模极大值原理识别故障行波波头(Modulus maxima principles identified wave head)

使用小波变换的图像边缘检测算法(use wavelet transform Edge Detection Algorithm)

对信号进行小波去噪再重构，针对不同分解层次的高频系数，采用分层阈值方式来量化高频系数。(Signal is carried out the wavelet denoising again reconstructed to quantify high-frequency coefficients, high-frequency coefficients for different levels of decomposition, hierarchical threshold.)

小波分析程序，用于小波包分析，小波树的建立，剪切，分解等等(Wavelet analysis procedures for the wavelet packet analysis, wavelet tree establishment, cut, break, etc.)

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)

小波变换测试，小波分解的级数设置为3级，可以实现数字图像的小波变化和逆变化。测试代码请使用512*512灰度图像(The wavelet transformation test, wavelet decomposition series is set to 3, digital image wavelet changes and reverse changes.)

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.)

一种基于改进谱减法的语音去噪新方法，对于想学习谱减法的同学有很大的帮助(A kind of based on improved spectral subtraction speech denoising, a new method to want to learn the spectral subtraction classmates have a lot of help )

对地震数据进行gabor反褶积处理，有实例验证方法，简单易懂(The seismic data are processed by Gabor deconvolution.There are examples of methods to verify, easy to understand)

基于小波变换的电压暂降定位 利用模极大值原理实现暂降起止时刻的准确检测(voltage sag lacote based on wavelet transform Used to achieve maximum modulus principle sag beginning and ending time of the accurate detection)