harrlike-for-face-dectection

说明：  逼近线性模型中Ｍ估计分布的随机加权自助法，在一般的条件下证明了这种方法是强有效的。 (Approximate linear model estimated the distribution of M random weighted bootstrap, in general terms that this approach is strong and effective.)

这是一个很好的，比较简单的高斯信道仿真程序，里面包括安全信道容量。本程序通过10000次信道采样获得平均信道容量。(It is a good code for capacity in Gauss channel.)

The matlab based code for energy detection of a receiver

介绍了newton插值的Mtlab程序，程序简单易懂，有助于对newton插值的了解。(Introduction of the newton interpolation Mtlab procedures, the procedures simple and easy to understand, contribute to the understanding of newton interpolation.)

功率谱估计是利用有限长的数据估计信号的功率谱，广泛应用于各个领域。功率谱估计主要分为经典谱估计与现代谱估计。常用的经典谱估计方法有周期图法，相关法，周期图的改进法，常用的现代谱估计方法有最大熵谱估计，AR模型，MA模型，ARMA模型。经典谱估计适用于长序列的信号，其主要缺陷是描述功率谱波动的数字特征方差性能差，频率分辨率低，现代谱估计适用于短序列的信号，旨在改善谱估计的分辨率，并将其应用于实际地震资料的谱分析。 (Power spectrum estimation is the use of a finite length data to estimate the power spectrum of the signal, widely used in various fields. Power spectrum estimation is divided into classic and modern spectral estimation spectral estimation. Commonly used methods of classical periodogram spectrum estimation method, the relevant law, the cycle graph Improvement Act, commonly used in modern spectral estimation methods have maximum entropy spectral estimation, AR model, MA model, ARMA model. Classical spectral estimation applied to signal a long sequence, its main drawback is the fluctuation power spectrum describing digital signature variance performance is poor, the frequency resolution is low, modern spectral estimation applied to signal short sequences designed to improve spectral estimation resolution, and The analysis applied to real seismic data spectrum.)

Lucas-Kanade part 2 对计算机视觉和机器学习很有帮助 详细论文和代码在文章的附录中有详细地址 很不错 (Lucas-Kanade part 2 of the computer vision and machine learning for more helpful articles and code in the article addresses in detail in the appendix is ​ ​ very good)

Learning Automata Algorithms A collection of machine learning programs which contains some of Learning Automata algorithms such as Tsetline, Krinisky, Krylov, LRI, LIP, LRR, LReP, SoftMax, SampleAverage and Random strategy. All of these developed in MATLAB 6.5

经典控制论稳定性判定算法，基于matlab(The cybernetics stability decision algorithm, matlab)

matlab遗传算法工具箱解函数优化问题应用实例(matlab genetic algorithm toolbox solution function optimization application examples)

说明：  AP聚类算法的源代码，基于matlab程序，有较详细解说(AP clustering algorithm source code, based on matlab program, a more detailed explanation)