QR矩阵分解算法，奇异值分解算法，可以验证。

简单的adaboost程序，面临着MIT库，利用Haar特征进行训练

简单的二叉树实现-achieve simple binary tree

陀螺进动仿真模型，可以修改窗口参数，使用起来很方便。-gyroscope precession simulation model can modify parameters of the window, was easy to use.

自适应算法的程序，用matlab语言编写，属于现代信号处理方法。-Adaptive algorithm of the program, with the matlab language, belongs to modern signal processing methods.

这是数据挖掘算法，基于FP-tree。适用于静态数据库中频繁项的挖掘。需要扫描两次数据库。并且不会产生候选项集。较Apriori算法效率较高。

这个函数ObjectDetection Viola-Jones中检测的实现框架。在这个框架Haar-like特性用于快速目标检测。它支持训练分类器OpenCV的XML文件,可以在opencv.willowgarage.com上下载作为OpenCV的一部分软件

自己写的一个Bayes分类器的matlab程序，比较简单。 使用方法 >> [ train_x, train_y ] = readdata("train_data.txt" ); >> [ test_x, test_y ] = readdata("test_data.txt" ); >> [mode]=MyBayes_train( train_x, train_y); >> [ acurracy, predict_y]=MyBayes_test( test_x, test_y, mode);

一个基本的简单库，用遗传算法求解车辆路径问题和货郎担问题，Java 编程语言编写的。

MSLSⅠ多步递推最小二乘法 Msls分三步对系统和噪声模型进行辨识，采用脉冲序列作为辅助系统模型，用计算输出数据；用原输出数据计算,用递推最小二乘方法分别对系统参数和模型参数进行估计。 -MSLS Ⅰ recursive least squares multi-step Msls three steps on the system and noise model identification, the use of pulse sequence as a supplementary system model, the calculation of the output data with the original output data, the use of recursive least squares method on system parameters, respectively, and model parameters estimated.

Individual files are available in the following links: Bessjy -- Bessel functions Jn and Yn for real argument and integer or real order. Bessik -- Modified Bessel function In and Kn for real argument and integer or real order. CBessjy -- Bessel functions Jv and Yv for real or complex arguments and real order. CBessik -- Modified Bessel functions Iv and Kv for complex arguments and real order. -Individual files are available in the following links: Bessjy- Bessel functions Jn and Yn for real argument and integer or real order. Bessik- Modified Bessel function In and Kn for real argument and integer or real order. CBessjy- Bessel functions Jv and Yv for real or complex arguments and real order. CBessik- Modified Bessel functions Iv and Kv for complex arguments and real order.