该文章是一篇博士论文，主要做了对小波变换的应用研究和程序实现，具有很强的理论性。...

行波-Traveling Wave

本程序是一维与两维小波算法的例子-this procedure is one-dimensional and two-dimensional examples of wavelet algorithm

实现了方波、正弦波、三角波的输出，同时在LCD模块中用状态机的方法实现LCD的对应显示：当输出正弦波，LCD显示“SIN”；当输出方波，LCD显示“REC”；当输出三角波，显示“TRI”；复位和其它位置波形显示“UNI”。-Realize a square wave, sine wave, triangle wave output, while in the LCD module using the state machine approach to achieve the corresponding LCD display: When the output sine wave, LCD display

用matlab编写找到向量维度的波峰波谷的值.-Prepared using matlab to find vector value of the dimension of the peaks and valleys.

利用小波变换的图像处理程序-using wavelet transform the image-processing program

常用的小波变换、傅立叶变换、离散余弦变换、图像旋转、平移、缩放类模块，用户只需运行时只需调用相应的模块，这是我从我们开发的系统中剥离出来的类模块，供大家使用，希望大家能喜欢！-commonly used wavelet transform, Fourier transform, discrete cosine transform, image rotation, translation, scaling type module, users can run only when the corresponding module called, this is my from our development of the system spin-off from the class module for everyone to use, I hope you will like!

台湾朝阳大学关于小波变换的一篇论文,对学习小波的应该有帮助.

有限冲击响应编程源代码,数字信号处理的基础知识.-programming source code, digital signal processing of the knowledge base.

小波变换与工程应用（超星格式电子书籍）-wavelet transform and Engineering Applications (Superstar format e-books)

关于二维小波变换的程序 [精华] 说明：此算法重在概念，速度并不是很快。因为FOR循环的缘故。此程序从循环矩阵的观点出发，把圆周卷积和快速幅里叶变换建立了联系。实现了分解和无失真重构。它只做了一层分解，即将256x256图形分解成为64x64的四个图形，避免了使用WKEEP()的困惑。主要思想为用小波滤波器族构造正交阵W,变换写为B=W*A*W ,反变换为：A=W *A*W,这与所有正交变换无异。W为循环正交矩阵，因此可用FFT实现快速运算，难点就在重构矩阵上。若用矩阵概念明确，一个共扼转置可以搞顶。但FFT的使用必须找到与分解序列的关系。-on Wavelet Transform procedures [best] Note : This algorithm important concept is not speed quickly. Because FOR cycle nowadays. This program cycle from the point of view of Matrix, circular convolution and fast Fourier transform is established links. To achieve the decomposition and reconstruction without distortion. It only had one decomposition, 256x256 graphics will be 64x64 decomposition of the four graphics, avoiding the use of WKEEP () confusion. The main idea of using wavelet filter generator orthogonal array W, write to transform B = W* A* W, anti-Transform : A = W* A* W, which is orthogonal transformation all the same. W cycle orthogonal matrix, can be used to achieve rapid FFT computation, on the dif