DG

解读matlab之小波库函数，对matlab中关于小波的主要函数进行的解读，并编写了源码(Interpretation of the wavelet matlab library function, wavelet matlab on the main function of interpretation, and the preparation of source)

这个程序的主要功能是对彩色图像进行叠加计算。(Superposition of color images)

hanso is a code that you can use with hiffoo and improve its performance

自己编写的图像增强程序，提供MATLAB的源码下载和实例，适合初学者进行学习。(I have written image enhancement procedures, and provide examples of MATLAB source code download, suitable for beginners to learn.)

multivariate analysis tool

NTKL法可以同时检测光谱异常点、参考数据异常点及其他们共同的异常点，该方法的基本思路是基于蒙特卡洛采样，随机将样本集划分为校正集与预测集，用校正集建模，并对没参与建模的样本进行预测误差计算，进行几千次这样随机采样，每个样本点都可得到其预测误差分布。如果奇异样本在校正集中，整个模型的质量将受到影响；相反，如果奇异样本在预测集中，仅此样本的预测结果受到影响。(NTKL method can simultaneously detect abnormal spectrum and abnormal reference data points and their common abnormal point, the basic idea of this method is based on the monte carlo sampling, sample set random be divided into calibration set and prediction set, using correction modeling, modeling and participated in the samples of the prediction error calculation, a thousands of times that of random sampling, each sample point can be obtained the prediction error distribution.If singular samples in correction, the model of quality will be affected.Singular samples in predicting concentration, on the contrary, if only for the sample prediction results are affected.)

说明：  已知一组数据,如何用matlab画出它的概率密度分布图,给出具体程序 并且得出分布图后,如何对图进行积分,进而得到分布函数(Given a set of data, how to draw it with matlab probability density distribution maps, specific procedures are given and draw maps, how points on the graph, and then by distribution function)

计算癫痫脑电非线性动力学之一的lyapunov指数(calculated EEG epilepsy nonlinear dynamics, one of the lyapunov index)

用来求解非线性系统周期解的打靶法，程序简单易学。(The shooting method is used to solve the nonlinear system, periodic solution, the program easy to learn.)

刘宝碇《不确定规划及应用》第4章例4.2的matlab程序,58页。内容简单，但可以有效的帮助初学者理解随机模拟的原理。(Liu anchor " uncertain Planning and Applications" in Chapter 4 Example 4.2 matlab program, 58. Content is simple, but can effectively help beginners understand the principles of stochastic simulation.)