MLI3Niveaux-(1)

这是 Andrew Ng 机器学习讲义《Reinforcement Learning and Control》,包含了离散和连续MDP的内容，比官网的课件全。（官网的缺乏连续MDP部分）(This is Andrew Ng Machine Learning Materials " Reinforcement Learning and Control" , contains a discrete and continuous MDP content than the official website of the courseware whole. (Official website of the lack of continuous MDP section))

利用meanshift1算法实现视屏目标的跟踪，包含全套程序，并配有示例视屏。(Meanshift1 algorithm to track the use of screen targets, including a full program, and with a sample screen.)

Fourier Transforms using Matlab

说明：  forward处理程序，使用于煤炭、石油、天然气行业(forward processing procedures used in coal, oil, gas industry)

对于具体实验时，通常不是先给出函数的解析式，再进行实验，而是通过实验的观察和测量给出离散的一些点，再来求出具体的函数解析式。又因为测量误差的存在，实际真实的解析式曲线并不一定通过测量给出的所有点。最小二乘法是求解这一问题的很好的方法，本实验运用这一方法实现对给定数据的拟合。(For specific experiments, usually not first given function analytic formula, and then experiment but given by the experimental observation and measurement of a number of discrete points, and come back to find the specific function analytic formula. And because the presence of measurement error, the actual real analytic curve does not necessarily pass through all points of measurement given. The least squares method is a good way of solving this problem, the experimental use of this method of fitting the given data.)

The basic difference from the variants described above lies on the formation of the second component of the PSO algorithm (related with the personal best solution)

《Sparse and Redundant Representations：From Theory to Applications in Signal and Image Processing》Michael Elad的电子书，讲稀疏表示及其应用(《Sparse and Redundant Representations：From Theory to Applications in Signal and Image Processing》Michael Elad )

这是个cofdm的仿真程序，可以运行，界面较好，可以看到各个过程的数据变化(This is a simulation program, can cofdm operation, interface is good, can see various process data changes)

本书系统地介绍了生物医学数据分析的相关基础知识和主要的分析方法，并通过 MATLAB 对大量的 生物医学数据分析的实例进行实现。全书共分为 7 章：第 1 章绪论；第 2 章 MATLAB 应用基础；第 3 章 医用数学基础及其 MATLAB 实现；第 4 章多变量分析；第 5 章时间序列分析；第 6 章生物信息学基础； 第 7 章生物医学数据的检索方法。 (This book introduces the relevant basic knowledge and analysis of biomedical data analysis, and analysis of biomedical data through MATLAB instance implemented. The book is divided into seven chapters: Chapter 1 Introduction Chapter 2 based on MATLAB applications Chapter 3 Medical mathematical foundation and its MATLAB implementation Chapter 4 multivariate analysis Chapter 5, time series analysis Chapter 6 bioinformatics Chapter 7 of the foundation biomedical data retrieval methods.)

matlab求解热传导方程的几个例子，有注释，适合初学者(matlab solving a few examples of the heat conduction equation, with notes, suitable for beginners)