turboprog

matlab 函数命令大全，包括各种函数及基说明，使用方便。(matlab function command Daquan, including a variety of functions and the base note, easy to use.)

使用matlab实现多学科设计优化中目标层解分析法，比较形象的描述了问题的求解。(Matlab realize the use of multidisciplinary design optimization of the target layer solution analysis, comparing the image of a description of the problem solving.)

对实际测得坐标实现圆拟合，前提是几何形状近似圆(The actual measure coordinates are fit to a circle, provided that that geometry approximates the circle)

利用经典Jakes模型生成时间频率双选信道，自己写的，已对各参数进行标注(Using the classical Jakes model to generate time-frequency dual-channel selection, write, and has marked the various parameters)

基于LS-SVM的多分类器的工具箱，版本的1.8的。该工具箱很好用，里面的分类我用过，效果比SVM强(LS-SVM classifier 1.8 version of the toolkit)

说明：  计算加速器频谱，可以显示加速器频谱书面 加速器频谱，可以显示加速器频谱书(Compute accelerator spectrum, the spectrum can show a written accelerator accelerator spectrum, the spectrum can be displayed accelerator book)

this is the matlab program of dvb transmission and reception of ofdm signals

CMOS集成电路基础知识，CMOS集成电路的接口电路，CMOS集成电路使用注意事项 (Basic knowledge of CMOS CMOS integrated circuit, integrated circuit interface circuit, CMOS integrated circuit use matters needing attention )

运用matlab的过程中的一些注意地方，为一个附件(Matlab course of the use of some of the attention of local, as an annex)

Advances in data collection and storage capabilities during the past decades have led to an information overload in most sciences. Researchers working in domains as diverse as engineering, astronomy, biology, remote sensing, economics, and consumer transactions, face larger and larger observations and simulations on a daily basis. Such datasets, in contrast with smaller, more traditional datasets that have been studied extensively in the past, present new challenges in data analysis. Traditional statistical methods break down partly because of the increase in the number of observations, but mostly because of the increase in the number of variables associated with each observation. The dimension of the data is the number of variables that are measured on each observation.