program

matlab讲义，书中含有大量的matlab例子及其源程序。(matlab lecture, the book contains a lot of matlab examples and source code.)

EMD的Toolbox及使用方法 经验模态分解（Empirical Mode Decomposition, 简称EMD）是由美国NASA的黄锷博士提出的一种信号分析方法.它依据数据自身的时间尺度特征来进行信号分解, 无须预先设定任何基函数。这一点与建立在先验性的谐波基函数和小波基函数上的傅里叶分解与小波分解方法具有本质性的差别。正是由于这样的特点, EMD 方法在理论上可以应用于任何类型的信号的分解, 因而在处理非平稳及非线性数据上, 具有非常明显的优势。所以, EMD方法一经提出就在不同的工程领域得到了迅速有效的应用, 例如用在海洋、大气、天体观测资料与地震记录分析、机械故障诊断、密频动力系统的阻尼识别以及大型土木工程结构的模态参数识别方面。本工具书主要分以下几个部分：导论、非稳态信号介绍、一维时频信号分解、二维时频信号分解、时频影像信息提取等。 (Time frequency toolbox for use with MATLAB The Time-Frequency Toolbox has been mainly developed under the auspices of the French CNRS (Centre National de la Recherche Scientifique). It results from a research effort conducted within its Groupements de Recherche ”Traitement du Signal et Images” (O. Macchi) and ”Information, Signal et Images” (J.-M. Chassery). Parts of the Toolbox have also been developed at Rice University, when one of the authors (PG) was visiting the Department of Electrical and Computer Engineering, supported by NSF. Supporting institutions are gratefully acknowledged, as well as M. Guglielmi, M. Najim, R. Settineri, R.G. Baraniuk, M. Chausse, D. Roche, E. Chassande-Mottin, O. Michel and P. Abry for their help at different phases of the development.)

已修改调试，可以运行.有图像结果，易以观察结果(it can be used in matlab, because it have amend.)

Regularized Linear Regrassion and Bias v.s. Variance

说明：  数值计算牛顿迭代法的matlab源程序 说明如下： ％fun----input,the part as the form of f(x) in the equation f(x)=0 ％ ini----input,sets the starting point to ini ％ err----input,sets admissible error ％ sol----output,returns the root of equation(Numerical calculation of the Newton iteration matlab source described as follows: fun---- input, the part as the form of f (x) in the equation f (x) = 0 ini---- input, sets the starting point to ini err---- input, sets admissible error sol---- output, returns the root of equation)

we present a practical link adaptation algorithm for MIMO-OFDM systems. The proposed solution is based on sounding the channel periodically and choosing the optimal mode that will maximize the throughput or energy efficiency (EE) while satisfying the application’s quality of service (QoS) requirements. In addition, we address practical problems such as the computational complexity of the algorithm and determination of sounding period by novel closed form solutions and iterative algorithms. Realistic link level simulations confirm that the proposed solution achieves significant improvement over existing link adaptation algorithms when the aim is to maximize the throughput, and provides orders of magnitude gain in energy efficiency compared to poorly chosen fixed modes when used for energy efficiency maximization purposes. The resulting algorithms are implemented on a real time MIMOOFDM testbed, and we report on the experimental results.

文件包括matlab教程的两部分内容：1.word文档，各章的详细内容。2.各章例题的matlab源程序。(File includes matlab tutorial two parts of contents:1.word document, each chapter of detailed content. 2.matlab source program of each chapter.)

随机骨料生成（Matlab建立的混凝土骨料随机投放模型）(concrete bone 2d model)

小波包分析提取振动信号中的特征频率，计算十字叉丝的在不同距离的衍射图像,可直接计算得到多重分形谱。( Wavelet packet analysis to extract vibration signal characteristic frequency, Calculation crosshairs diffraction image at different distances, It can be directly calculated multi-fractal spectrum.)

仿真程序：首先需要用一个随机发生器产生（0.1）内的均匀随机数，然后再将该序列映射到对应的幅度电平｛Am｝。然后将这个范围再分成4个相等的区间，这些子区间分别对应于4个信号比特的符号00，01，10，11。检测器观察到r=Am+n，并且计算r和4种可能传输的信号幅度之间的距离，它的输出Bm就是相应于最小距离的信号电平。Bm与真正的的传输信号幅度比较，差错计数器用来对检测器产生的差错计数。(Simulation program: first need to use a random generator (0.1) the uniform random number, then the sequence is mapped to the corresponding amplitude level {Am}. Then this range has been divided into four equal intervals, these sub-intervals corresponding to four signal bits of the symbol 00,01,10,11. Detector observed r = Am+ n, and calculate r and 4 possible transmission distance between the signal amplitude, its output corresponding to the minimum distance Bm is the signal level. Bm and the real rate of transmission of the signal comparison, error detection counter is used to generate the error count.)