Y649678

说明：  实现对离散信号的连续小波变换进行时频域分析，判断信号的稳定性(The continuous wavelet transform of the signal is analyzed in time and frequency domain)

说明：  小波变化代码，是比较好的测试向量，包括位平面编码和MQ(Wavelet transform code, is a better test vectors, including the bit plane coding and MQ)

小波变换去噪，软阈值和硬阈值，以及自己的设计的阈值函数来去噪，毕业设计全套。很全面的资料，绝对最全面的资料，我保证(Wavelet denoising, soft thresholding and hard thresholding, as well as design their own threshold denoising function, the design of a full set of graduation. Comprehensive information is absolutely the most comprehensive information, I promise)

FMCW调频连续波雷达的测距测角，可以得到很精确的幅值、频率、相位估计，有小波分析的盲信号处理。( FMCW frequency modulated continuous wave radar range and angular measurements, You can get a very accurate amplitude, frequency, phase estimation, There Wavelet Analysis Blind Signal Processing.)

这是一本关于高维(三维以上)小波的书，对做三维的朋友应该有参考价值，所以特意贡献出(This is one of the high-dimensional (3-D above) wavelet, the book right to do 3D friends should have reference value, So deliberately contributing)

小波神经网络实现短期电力负荷预测，神经网络模型及其BP学习算法。 (Wavelet neural network short term load forecasting, neural network model and BP learning algorithm.)

小波变换光谱数据预处理阈值平滑处理用于光谱数据(xiaobobianhuan yuchuli )

自己编写的基于指数遗忘快速算法改进的morlet小波变换程序(I have written forgotten fast algorithm based on the index improved wavelet transform morlet procedure)

希尔伯特变换和小波包结合的齿轮箱故障诊断方法，里面有具体的介绍小波包的分层方法，非常详细，可以下下来看看(Hilbert transform and wavelet packet of gearbox fault diagnosis method, there is detailed introduction inside the layered method of wavelet packet is very detailed, can down and have a look )

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.)