MATLAB

说明：  本人的一篇数字图像水印文章，一种基于图像最高有效位构造密钥的零水印算法（核心期刊），共大家参考。(A Kind of Non-watermarking Algorithm Based on MSB Structure Key )

说明：  在MATLAB环境下，实现对小波变换信号处理的有关试验(In the MATLAB environment, the realization of wavelet transform signal processing of the pilot)

说明：  多目标优化的例证，用粒子群算法做的。调试过，没问题，能用。(multi-objective ,PSO)

Introduction to Emacs LISP programming.

A direct search method instead of a coordinate descent iterative LMI algorithm

系统辨识，最小二乘法matlab仿真程序，非常实用(System identification, least squares matlab simulation program, very useful)

此源码是基于matlab编写的关于查找图像中图形的个数，及查找每个图形的重心并显示。(This source code is written in matlab based on the number of graphic image search, and find the center of each graph and display.)

适当选择辅助变量，使之满足相应条件，参数估计值就可以是无偏一致。估计辅助变量法的计算量与最小二乘法相当，但辨识效果却比最小二乘法好的多。尤其当噪声是有色的，而噪声的模型结构又不好确定时，增广最小二乘法和广义最小二乘法一般都不好直接应用，因为他们需要选用特定的模型结构，而辅助变量法不需要确定噪声的模型结构，因此辅助变量法就显得更为灵活，但辅助变量法不能同时获得噪声模型的参数估计。(Choose appropriate secondary variables, meet the relevant conditions and parameter estimate can be unbiased consistent. Estimated auxiliary variable method calculation and least square method is quite, but the identification effect is much better than the least square method. Especially when the noise is colored, and noise model structure and not sure, augmented the least squares and the generalized least squares method is generally not used directly, because they need to choose specific model structure, and auxiliary variable method does not need to make sure that noise model structure, so the auxiliary variable method is more agile, but not at the same time auxiliary variable method for noise model parameter estimation.)

这个程序关于语音信号的消噪，实现了一个基于最小均方误差算法的自适应噪声抵消器(This program about the speech signal de-noising, to achieve a minimum mean square error algorithm based on adaptive noise canceller)

这个函数返回n点2dw波段的傅里叶变换的DFT样本序列。通常情况下，以插值点的方式进行放大。(This function returns N point DFT samples of 2dw band of Fourier transform of a sequence. Typically, fft() returns N samples of Fourier transform ranging from 0 to 2pi. This function takes the N-point DFT samples and returns N-point samples corresponding to frequency band wc-dw to wc+dw.)