11111

在度量两个矩阵时，快速的度量函数能有效地提高检索效率，在此采用EMD度量函数(In the measure two matrix, fast measurement function can effectively improve the retrieval efficiency, in this the EMD measure function )

国外的一个用C实现的类似matlab数学库，功能貌似很强大，很多功能已经有源码了，喜欢C语言的人有福了。(Foreign matlab math library in C, the function looks like a very powerful, many functions have been source of the Blessed are those who like the C language.)

一个关于matlab优化工具箱GOT中的遗传算法函数（GA）和全局优化算法函数（Globalsearch）优化能力的小对比，前者寻优快，但是结果不稳定，在风电场协同有功出力优化上面甚至可能比不过传统的单个风机层面的优化。后者计算量大，耗时较长，但是每次计算结果稳定，较传统单台风机层面优化有少量的提升。Tips:1,本文风场的建模只是采用了PARK模型，实际风场的气动过程应该还要复杂一些，未经实际风场验证，权当是工程优化入门 2,单个风机层面的功率系数Cp参数来源于NREL 5MW模型，跟实际叶片气动性能有关，可靠性未知。3,这种风场级别的协同优化主要考虑尾流因而更加适用于地形较平坦的风电场。《基于风机运行参数协同设定的风电场有功出力优化》是部分由这个程序支撑的，欢迎交流。(The classical operation strategy of a wind farm works with a principle that each wind turbine converting as much aerodynamic power as available the incoming airflow. But this does not guarantee that the power converted by the whole wind farm be a maximum due to the wake effect. Unlike the conventional operation, this paper proposes the collaborative setting of the operation point of each turbine so that the overall production of the wind farm is maximized. The optimization is performed by Matlab Global Optimization Toolbox(GOT) based on a PARK wake model accompany with the area-weighted quadratic sum method. The strategy was proved applicable in many cases by sensitivity analysis. As an important side effect, the proposed method also allows decreasing the added turbulence, hence the mechanical load produced by wakes. As a consequence, the overall wind farm availability is increased. )

在MATLAB上用三角级数法对路面谱进行仿真，实现不同级数的路面谱的再现(Road spectrum model simulation using the trigonometric series (harmonic superposition method) in MATLAB, the reproduction of different levels of road spectrum)

基于ESPRIT算法的相干分布式多信号源的DOA估计(Distributed coherent signals DOA estimation based on the ESPRIT algorithm)

dds信号发生器，matlab7.0，dspbuilder7.0(dds signal generator, matlab7.0, dspbuilder7.0)

Compressive sampling is an emerging technique that promises to effectively recover a sparse signal from far fewer measurements than its dimension. The compressive sampling theory assures almost an exact recovery of a sparse signal if the signal is sensed randomly where the number of the measurements taken is proportional to the sparsity level and a log factor of the signal dimension. Encouraged by this emerging technique, this thesis briefly reviews the application of Compressive sampling in speech processing. It comprises the basic study of two necessary condition of compressive sensing theory: sparsity and incoherence. In this thesis, various sparsity domain and sensing matrix for speech signal and different pairs that satisfy incoherence condition has been compiled.

程序代码说明 图像中的欧拉数是图像识别等的重要特征参数，本程序是采用matlab计算图像中的欧拉数(Code description of the Euler number of images is important, such as image recognition feature parameters, the procedure is calculated using matlab image Euler Number)

这是规则化滤波复原的matlab代码，需要的可以作为参考(This is the matlab code regularization filter recovery, need can be used as a reference)

说明：  一些经典的Q-learning代码,用MATLAB语言编写，在MATLAB平台可运行(some easy Q-learning code)