MATLAB

（1）通过Simulink创建仿真模型；（2）配置Simulink模型相关参数；（3）通过C语言调用C Engine API，控制模型的运行，并进行结果分析；（4）掌握Simulink模型在分布式仿真环境中应用的要点与方法。 ((1) created by Simulink simulation model (2) configuration parameters of Simulink models (3) by C language called C Engine API, the control model run, and the results of analysis (4) control in a distributed simulation environment Simulink model points and methods of application.)

Tiva C 123 Application projects

此程序描述ＭＱＡＭ信道容量，详细内容关于８ＱＡＭ，１６ＱＡＭ，３２ＱＡＭ，６４ＱＡＭ的信道容量(This procedure describes the QAM channel capacity, details on 8QAM, 16QAM, 32QAM, 64QAM channel capacity)

最小二乘支持向量机，采用matlab编写，可以直接使用，SVM是经典的分类和预测算法。(Squares support vector machine, using matlab prepared, can be used directly, SVM is the classic classification and prediction algorithms.)

matlab svm 分类程序，适合7.0以上的版本(matlab svm classification procedures suitable version 7.0 or above)

matlab gui设计学习实例 实现小球旋转，反转，停止，调速等功能(example of matlab gui)

matlab2007a版本的使用教程和范例，包括book文件夹和m文件夹。(matlab2007a version of the use of tutorials and examples, including folders and m book folder.)

CUMCM 2011A 等高线CUMCM 2011A 等高线CUMCM 2011A 等高线CUMCM 2011A 等高线(CUMCM 2011A CUMCM 2011A CUMCM 2011A CUMCM 2011A CUMCM 2011A CUMCM 2011A CUMCM 2011A CUMCM 2011A )

实现边界正择性测量，可在MATLAB环境下运行(the border is optional measurement, in the MATLAB environment running)

efficient LBP Local binary patterns (LBP) is a type of feature used for classification in computer vision. LBP is the particular case of the Texture Spectrum model proposed in 1990.[1][2] LBP was first described in 1994.[3][4] It has since been found to be a powerful feature for texture classification it has further been determined that when LBP is combined with the Histogram of oriented gradients (HOG) descriptor, it improves the detection performance considerably on some dataset