FastAlgorithms

小波阈值法去噪的程序，其中有关于信噪比和均方根误差的公式(wavelet denoising)

这是基于小波变换的图像融合程序，附带融合图像(This is based on the wavelet transform image fusion procedures, fringe Image Fusion)

mimo_BP用于十字型阵列雷达，利用匹配滤波理论进行算法仿真(mimo_BP Used for cross-array radar, using matched filter theory for algorithm simulation)

说明：  小波变换用于脑电信号处理，可以很好的对脑电信号进行时频分析(Wavelet transform for EEG signal processing, can be very good for time-frequency analysis of EEG)

此示意程序用DWT实现二维小波变换 1.调原始图像矩阵 2.进行二维小波分解 3.分解结果显示 重构源图像及结果显示 (This indicated the procedure using two-dimensional wavelet transform DWT realize one. Transferred the original image matrix 2. To carry out two-dimensional wavelet decomposition 3. Decomposition results show that reconstruction of the source images and results show)

说明：  Curvelet变换是由一种特殊的滤波过程和多尺度脊波变换组合而成：本程序对彩色图像进行了curvelet变换从而实现图像去噪的效果。首先对图像进行子带分解；然后对不同尺度的子带图像采用不同大小的分块；最后对每个分块进行Ridgelet分析。(Curvelet transform is a combination of a special filtering process and multi-scale ridgelet transform. In this program, curvelet transform is applied to color image to achieve the effect of image denoising. First, the image is decomposed into sub-band; then the sub-band images of different scales are divided into different sizes; finally, each sub-band image is analyzed by ridgelet.)

图像小波变换，小波变换（wavelet transform，WT）是一种新的变换分析方法，它继承和发展了短时傅立叶变换局部化的思想，同时又克服了窗口大小不随频率变化等缺点，能够提供一个随频率改变的“时间-频率”窗口，是进行信号时频分析和处理的理想工具。它的主要特点是通过变换能够充分突出问题某些方面的特征，能对时间（空间）频率的局部化分析，通过伸缩平移运算对信号（函数)逐步进行多尺度细化，最终达到高频处时间细分，低频处频率细分，能自动适应时频信号分析的要求，从而可聚焦到信号的任意细节，解决了Fourier变换的困难问题，成为继Fourier变换以来在科学方法上的重大突破。(Image Wavelet Transform)

此程序用DWT(离散小波变换)实现二维小波变换(discrete wavelet transform )

针对滚动轴承信号的特点，构造脉冲响应小波，采用连续小波变换的方法提取滚动轴承故障信号，提出两种诊断方法。(For Rolling signal characteristics and tectonic pulse response wavelet using continuous wavelet transform to extract the rolling bearing fault signals, and proposed two diagnostic methods.)

此程序仿真了一个被污染了的信号源，然后通过小波去噪，成功取出了信号中的杂波(This procedure simulation has polluted the supply oscillator, then through the wavelet denoising, the success took out in the signal clutter )