matlab100examples

MATLAB优化应用书籍，书中详细讲述了MATLAB中优化方面，是一本难得的资料，书中有详细的案例和具体的操作过程是学习MATLAB优化的首选资料(MATLAB optimization of application of books, book detail in MATLAB, optimization, is a rare data, the book detailed the case and specific course of action is to learn MATLAB optimization of the preferred data)

最短路径问题（包括Floyd算法和避圈法）的matlab程序，较实用(Shortest path problems (including Floyd algorithm and avoid the circle method) matlab procedures, more practical)

Implementation of morphological shape decomposition algorithm (image processing)

时间序列分析，需要的额下来看看，求高人指导(Time series analysis, the amount needed down to look at, seek expert guidance)

Support for SD detector

层次模糊聚类的算法实现，一个用C或者C++写的kmeans算法，最新的聚类算法(Level fuzzy clustering algorithm, one using C or C++ written kmeans algorithm, the latest clustering algorithm)

自相关基音检测算法是语音信号处理的关键技术，算法的效率直接影响语音信号实时处理的质 量。(Autocorrelation pitch detection algorithm is the key to speech signal processing technology, a direct impact on the efficiency of algorithms in real-time speech signal processing quality.)

在基于前景检测的基于移动物体检测和车辆跟踪算法的实现中，针对广泛的应用来实现读取AVI文件，并将其分解为R，G和B组件。 执行各种操作并检测移动物体。 各个阶段的阈值决定了识别某些尺寸的移动物体的可能性。 移动物体也在其中跟踪。 MATLAB用于实现算法。 该算法用包含120帧的输入avi格式视频文件进行测试。 研究并实现了这些算法的各种应用。(In this foreground detection based moving object detection and vehicle tracking algorithm is implemented targeting a wide class of applications. An AVI file is read and it is decomposed into R, G and B components. Various operations are carried out and the moving objects are detected. Thresholds at various phases are decide the possibility of identifying the moving object of certain sizes. Moving objects also tracked in it. MATLAB is used for implementation of the algorithm. The algorithm is tested with input avi format video files consisting of 120 frames. Various applications of these algorithms are studied and implemented. Main focus is given on (unmanned aerial vehicle) UAV based and automatic traffic estimation applications)

学习压缩感知时自己编写的初步重建程序，有利于加深理解压缩感知的理论(Preliminary reconstruction program, write your own learning compressed sensing, a better understanding of the theory of compressed sensing)

similarity matching and conval filter 2d and 3d