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CUDA的MATLAB加速用户使用说明，帮助学习MATLAB的PCT(matCUDA for MATLAB PCT)

matlab拍照并图像处理，包含图像二值化，图像颜色分量提取等。(Matlab camera and image processing)

用移位寄存器产生M序列的MATLAB软件实现(M generated using shift register sequences MATLAB software)

decimal to binery converter

pso程序的源代码 pso程序的源代码-粒子群优化算法源程序 作者：FashionXu 一个pso程序的源代码。在vc.net2003下面通过。 建议：看代码之前，请先弄明白pso是怎么回事。然后请对应着来：程序中用Agent代表一只鸟，PSO代表鸟群。阅读源代码，不要顺着看，先看main(),然后按照出现的东西的顺序，一个一个得来，呵呵，纯粹是建议。(program s source code pso pso program s source code - source code on Particle Swarm Optimization: FashionXu a pso program source code. In vc.net2003 following through. Recommendation: look at the code before you figure out how the matter pso. Then please correspond to: Program using Agent on behalf of a bird, PSO representative of the flock. Read the source code, do not look down, look at the main (), then follow the order of things there, one by one, come, Oh, merely suggestions.)

使用matlab的m语言开发，功能为rake接收机的链路生成。其中包含短码生成成，业务信道长码生成，瑞利衰落信道代码， 哈达码变换，用户原始数据扩频和信道衰落 (Use Matlab m-language development, functional link generated for the rake receiver. Contains short code generated into business channel long code generation, code Rayleigh fading channels, Hadamard transform raw data of users spread spectrum and channel fading)

主成分分析的c++实现使用奇异值分解svd算法(Principal Component Analysis based on svd algorithm ，used c++)

用c编写的矩阵分解程序，对于不用 matlab的人来说，还是有一定用处(Prepared by c matrix factorization procedures, for people who do not have matlab, or there is some use)

MATLAB具有强大的科学计算功能, 含有大量多目标优化分析函数。依据技术将函数在 环境下进行调用, 进行多目标优化集成系统开发, 实现数据的自动输入和输出功能, 编制了MATLAB与VB的数据接口代码, 提出程序设计时应注意的问题。(MATLAB has powerful scientific computing functions, contains a large number of multi-objective optimization analysis function. Based technology will function in the environment calls for multi-objective optimization of integrated system development, automated data input and output functions, the preparation of the MATLAB data interface with the VB code, the program design should pay attention to the problem.)

Matlab interface for the image segmentation algorithm of Efficient Graph-Based Image Segmentation Pedro F. Felzenszwalb and Daniel P. Huttenlocher International Journal of Computer Vision, 59(2) September 2004.