27796744BDFMdq

OFDM WITH RAYLIEGH FADING

this is main program of tomography modelling

改进的粒子群算法在matlab中的应用，程序简单(Improved particle swarm algorithm in matlab, simple procedures)

编写M文件，创建如下图形窗口，分别绘制如下图所示的曲线。 （1）曲线y=sin(t)sin(9t)，要求采用红色，点线。横坐标取值范围[0~ ]，标注x轴、y轴并加标题。 （2）一组余弦曲线，其振幅分别为0.4，0.6和0.8。横坐标取值范围[0~2 ]。添加图例与标题。进入图形编辑状态，调整图例的位置。 （3）分别绘制peaks函数的曲面图和网格线图。对曲面图做平滑处理，并添加标题与colorbar。 (Write M file, create the following graphics window, curves were plotted as shown below. (A) the curve y = sin (t) sin (9t), require the use of a red dotted line. The abscissa in the range [0 ~  ], labeled x-axis, y-axis and a title. (2) a set of a cosine curve, and the amplitude was 0.4, 0.6, 0.8. Abscissa value range [0 ~ 2  ]. Add a legend and title. Into the graphical editing mode, adjust the position of the legend. (3) were drawn surface chart peaks function and grid line graph. Surface charts do for smoothing and add titles and colorbar.)

数码转换器的数字部分的matllab和simulink设计。对搞数模转换设计非常有用(design for ADC base on matlab and simulink。it is very good for you when you start your project。)

利用MATLAB基于人工势能场法进行避障，并分析避障过程中航行器与障碍物、目标点的距离(MATLAB is used to avoid obstacle based on artificial potential field method, and the distances between the vehicle and the obstacle and between the vehicle and the goal are analyzed)

用于实现粒子群算法的matlab工具包，带有一些测试函数(particle swarm optimization toolbox for matlab)

MATLAB中数值分析如拉格朗日插值、牛顿法求解方程组、LU分解等(MATLAB numerical analysis such as Lagrange interpolation, Newton' s method for solving equations, LU decomposition, etc.)

Barlow model for EEG

The use of fingerprints for identification has been employed in law enforcement for about a century. A much broader application of fingerprints is for personal authentication, for instance to access a computer, a network, a bank-machine, a car, or a home. The topic of this chapter is fingerprint verification, where "verification" implies a user matching a fingerprint against a single fingerprint associated with the identity that the user claims. The following topics are covered: history, image processing methods, enrollment and verification procedures, system security considerations, recognition rate statistics, fingerprint capture devices, combination with other biometrics, and the future of fingerprint verification.