Adaptive-filter

matlab 40个案例分析 和60个程序代码，很详细，值得入手(matlab 40 case studies and 60 program code, in great detail, it is worth starting)

一个著名简单的信息隐藏程序Contraband 9i (for Win311 or up - download-size 245K).rar(Information Hiding a well-known simple procedures Contraband 9i (for Win311 or up- download-size 245K). Rar)

主成分分析并用散点图分析前三个主成分M代码，请指教。(Principal component analysis and scatter analysis of the first three principal components M code, please advice.)

MATLAB基础讲解 适用于初学者 学会MATLAB不是问题 简单易懂 适用性强(MATLAB for beginners to learn to explain the basis of MATLAB is not a problem easy to understand applicability)

说明：  使用人工神经网络（ANN）实现手写数字体识别(Handwritten digit recognition)

基于matlab的信道仿真。包含了信道建模、qpsk调制解调、ofdm技术等等。(Channel simulation based on matlab. Contains the channel modeling, qpsk modem, ofdm technologies.)

高斯加性白噪声下采用MPSK调制的系统BER性能分析(High places like the white noise of the adoption of MPSK modulation system BER performance analysis)

电机转子台，断条缩孔的计算等，MATLAB等(Rotor sets, Breaking Shrinkage calculation, MATLAB, etc.)

用matlab编写的用于描述L系统(植被仿真)的源程序，文件夹中包括描述其理论的基本文献(Using matlab for the description of the L system (vegetation simulation) of the source folder, including a description of the theoretical literature)

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.)