BE-CO-RO-1991

基于小波变换模极大的多尺度图像边缘检测matlab源代码(based on wavelet transform modulus maxima of multiscale edge detection Matlab source code)

利用全局去噪和分层去噪实现信号的小波去噪，实现成功(Implementation of wavelet denoising, global denoising and level-dependent denoising)

用小波方法把脑电信号进行频段分解，并画出图形(Using wavelet method to decompose the eeg signals into frequency bands, and draw the graph)

数字全息和计算程式 计算全息图的制作和再现过程主要分为以下几个步骤： 1抽样。得到物体或波面在离散样点上的值。 2.计算。计算物光波在全息平面上的光场分布。 3.编码。把全息平面上光波的复振幅分布编码成全息图的透过率变化。 4.成图。在计算机控制下，将全息图的透过率变化在成图设备上成图。如果成图设备分辨率不够，再经光学缩版得到实用的全息图。 5.再现。这—步骤在本质上与光学全息图的再现没有区别。 (Digital Holography and CGH for calculating the production and reproduction process is divided into the following steps: 1 sampling. Be objects, or wavefront-like point in the discrete value. 2. Calculated. Calculation of complex light plane in the holographic optical field distribution. 3. Coding. The hologram plane the complex amplitude distribution of light into a hologram coding changes in the transmittance. 4. As Fig. Under the control of the computer, the hologram transmittance change in the mapping device mapping. Mapping equipment, if not resolution, then reduced by the optical version of a hologram to be practical. 5. Reproduction. This is- these in essence a hologram and the optical reproduction is no different.)

信号处理小波分析 1)计算信号的小波变换。 2)求出模极大曲线。 3)计算其中两个奇异点的Lipschitz指数。 (Signal processing wavelet analysis 1) the calculation of wavelet transform signals. 2) calculated curve of modulus maxima. 3) the calculation of which two singular points of Lipschitz index.)

小波神经网络,实现曲线拟和，数据分类，故障诊断，学习速度快于传统BP。(Wavelet neural network, and realize curve fitting, data classification, fault diagnosis, learning faster than the traditional BP.)

余弦变换-DCT。好用的小波变换方法程序。(Cosine transform-DCT. Use of wavelet transform.)

说明：  基于小波变换阈值去噪的MATLAB源代码（包含小波包去噪程序）(threshold based on wavelet transform Denoising MATLAB source code (including wavelet denoising packet procedure))

一种新的瞬时频率估计方法，用到了同步压缩短时傅里叶变换的高阶形式(This MATLAB package is a collection of scripts allowing to generate figures in the paper [1]. This paper puts forward a generalization of the short-time Fourier-based Synchrosqueezing Transform using a new local estimate of instantaneous frequency. Such a technique enables not only to achieve a highly concentrated time-frequency representation for a wide variety of AM-FM multicomponent signals but also to reconstruct their modes with a high accuracy.)

实现离散余弦(TCD)变换(achieve discrete cosine (TCD) Transform)