matlab

A generic controller architecture for intelligent robotic systems

MATLAB7_0基础教程_清华大学 对于初学MATLAB的人有很好的指导作用(MATLAB7_0based tutorial _ Tsinghua University)

Matlab_曲面插值和拟合，dajie可以看看(something about Matlab_b-spline)

1、熟悉LTE网络体系架构及接口； 2、掌握DBS3900单站数据配置整体流程； 3、掌握DBS3900单站全局数据配置步骤； 4、掌握DBS3900单站全局传输数据配置命令及参数含义； 5、掌握DBS3900单站无线层数据配置命令及参数含义； 6、理解BBU LMPT单板电口IP至MME IP地址对应意义（指向控制面--SCTPLNK）； 7、理解BBU LMPT单板电口IP与S-GW IP地址对应意义（指向用户面---IPPATH）； 8、理解扇区、小区的概念及二者的关系、 9、会将MML命令行制作成脚本数据。 ( A familiar LTE network architecture and interfaces 2, master data configuration DBS3900 single station overall process 3, master DBS3900 single station Global Data configuration steps 4, master DBS3900 single station global configuration commands and parameters of data transmission meaning 5, master data DBS3900 single station radio layer configuration commands and parameters meaning 6, understanding BBU LMPT board electrical interface IP to the MME IP address corresponding meaning (pointing control surfaces- SCTPLNK) 7, understanding BBU LMPT board electrical interface IP and S-GW IP address corresponding meaning (pointing to the user plane--- IPPATH) 8, understanding the sector, community and the relationship between the concepts, 9, will be made ​ ​ into MML command line script data.)

matlab课程编程【谷速软件】matlab带板的测试图像(test image matlab programming courses [Valley] matlab software speed with board)

是一个二乘二天线的多路复用的解码程序，利用Vblast算法来实现的，(Is a second antenna multiplexing二乘decoding procedures, the use of algorithms to achieve the Vblast.)

数学建模迪卡斯特拉算法，最短路问题图论的应用(Mathematical modeling Ducasse Terra algorithm)

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models.

mkL 多核学习，介绍的很详细，附有论文地址，包括所有相关的代码(mkL multicore study, described in great detail, with papers address, including all related code)

说明：  基于粗糙集属性约简的算法，不错，可以看看(Rough set attribute reduction algorithm, a good)