vc wrote realize wavelet processing, filtering, restoration, integration, such a...

％ Program from 移动传播环境-理论基础、分析方法和建模技术 杨大成编著 机械工业出版社 2003 ％ Program from pp.280~281 附录B 成形滤波法 - Program from mobile broadcasting environment- the theoretical basis for analysis and modeling techniques edited by Yang Dacheng Machinery Industry Publishing House 2003 Program from pp.280 ~ 281 Appendix B forming filtering method

采用多种小波基的离散小波变换源码-Wavelet basis using a variety of discrete wavelet transform source

dwt小波变换，用于对图像的处理与压缩-dwt wavelet transform, for the image processing and compression

小波神经网络,输出节点数为:J个；输入节点数为：I个-wavelet neural network, the output nodes : J; Input nodes : I-

一个关于图像边缘检测的实用程序-A practical program for image edge check

小波十讲，是一本世界范围公认的经典学术名著,是当代数学著作中一本影响巨大的绝妙好书-Wavelet

小波变换源代码，vc开发，对研究小波变换的人士来说，这是一个不错的基础程序。-Wavelet Transform source code, vc development, the study of wavelet transform people, this is a good basic program.

lifting scheme指南-lifting scheme Guide

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

此程序用提升法实现第二代小波变换,采用时域实现,步骤先列后行-This procedure used to enhance law to achieve the second-generation wavelet transform, using time-domain realization of the first steps out later