Matlabwaveenergy

一种用于尿沉渣图片的分割方法，先用小波变换和形态学，再使用边缘检测和阈值分割(urine for a picture segmentation method, use wavelet transform and morphology, re-use of edge detection and thresholding segmentation)

基于提升格式的整数小波变换及其编解码( And its arranges based on the promotion form integer wavelet transformation decodes )

几种小波阈值函数去噪的程序及其运行结果比较(Several wavelet threshold denoising function to run the program and its results more)

java小波变换的实现，包括哈尔小波，以及在这基础上改进的小波实现。(The implementation of Daubechies wavelets.)

在实数域 ,对称、 正交的紧支集非平凡单小波基不存在 ,而多小波把紧支集，对称性、 正交性完美地结合在一起 ,使小波理论从标量扩展到矢量范畴。利用上述特点将多小波变换应用于 SAR 图像压缩。(In the real fields, symmetric, orthogonal set of nontrivial compactly supported wavelet basis does not exist alone, but more than the compact support wavelet, symmetry, orthogonality perfect combination, So wavelets theory extended Dao vector from scalar context. Use of these features will be more than SAR image compression wavelet transform.)

本程序为小波包能量计算程序，根据相关资料，自己编写，计算感兴趣的频带能量，程序懂得人稍作修改就可以运行( U672C u7A0B u5E8F u4E3A u5C0F u6302 u803F0 u0B1 u7B97 u7A0B u5E8F uFF0C u6839 u636E u76R8 u5173 u8D44 u6599 uFF0C u81EA u5DF1 u7F16 u5199 UFF0C u8BA1 u7119 u6119 u5113 u8E1 u7684 u9891 u5E26 u80FD u91CF uFF0C u7A0B u5E8F u61C2 u5F97 u4EBA u7A0D u4F5C u4FEE u6539 u5C31 u53EF u4EE5 u8FD0 U884C)

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matlab的小波包分解应用于机械振动信号的故障分析(Used in failure analysis of mechanical vibration signals based on the Matlab wavelet packet decomposition)

小波变换的程序包括小波变化 小波分解小波包分解程序(Wavelet transform procedures include wavelet transform wavelet decomposition wavelet packet decomposition program)

说明：   这是一个用小波神经网络进行非线性函数逼近的例子，拟合效果非常好，保证能运行！有详细注释！我是参考《青岛海洋大学学报》 2001年第1期 一种基于BP算法学习的小波神经网络编写的，大家可以针对原文更好的理解我的程序！(This is a wavelet neural network with nonlinear function approximation example of fitting results is very good, guaranteed to run! Detailed Notes! I refer to Journal of Ocean University of Qingdao，2001 ，“a learning algorithm based on BP wavelet neural network ”, you will understand me better for program!)