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用MATLAB编程实现实现滤波，与数字信号处理相关(Implementing filtering)

用小波神经网络变换对时间序列信号进行预测，并做了测试，效果很好，请参考(Transform using wavelet neural network to predict the time series signal, and do a test with good results, please refer to)

说明：  关于小波变换的ppt，有用的可以下载看看(Ppt on Wavelet Transform)

用于进行小波变换，对原始的光谱图像数据进行预处理(Used wavelet transform, the original spectral image data preprocessing)

现代控制理论，卡尔曼滤波器设计，simulink控制仿真(Modern control theory, Calman filter design, Simulink control simulation.)

小波变换，小波去噪，包含多种去噪方法，模极大值，自适应，阈值去噪(Wavelet transform, wavelet denoising, including multiple Denoising, modulus maxima, adaptive thresholding)

此代码是用在被成为数学魔法师的MAPLE软件上运行的。此代码清晰的描述了欧拉公式的图象变换。以及如何在MAPLE里解欧拉公式。(This code is used in the magician to become the MAPLE mathematical software running. This code describes a clear image transform Euler formula. And how to MAPLE Euler formula in solution.)

　　　作为一种新型的有效的版权保护手段，数字水印技术倍受人们的关注。数字水印主要是通过在原始资料中嵌入秘密信息——水印,来证实资料的所有权。本文介绍了数字水印技术的基本原理及其分类，然后对数字水印讨论了一种基于LSB的数字图像水印算法,最后利用MATLAB7.6对这一算法进行了实现。(As a new effective means of copyright protection, digital watermarking technology much attention. The digital watermark secret information- the watermark embedded in the raw data, to prove ownership of the data. This article describes the basic principles of their classification of digital watermarking technology and digital watermarking digital image watermarking algorithm based LSB, and finally the use of this algorithm matlab7.6 achieve.)

使用小波变换进行图像去噪，对得到的高频部分利用软阈值和硬阈值法去噪(Image denoising using wavelet transform, the high frequency part by the use of soft threshold and hard threshold denoising)

本程序应用小波变换进行电力系统的在线监测。电力系统在线监测中的检测信号含有大量的背景噪声，不便于检测。应用小波变换解决这一问题。程序中应用db3小波对信号进行5层分解，并得出了各层的细节信号与逼近信号。(This procedure based on wavelet transform power-line monitoring system. Online monitoring of power system test signal contains a lot of background noise, not easy to detect. Application of wavelet transform to resolve this problem. Application procedures for db3 wavelet signal decomposition layer 5, and arrive at different levels of detail signal and approximation signal.)