anchal

众多恒虚警检测（CFAR）算法都是基于单元平均（CA:Cell Avarage）的方法，该算法需要较大的运算量。本程序给出了基于有序统计（OS:Order Statistic）的CFAR检测算法，弥补了CA_CFAR检测算法的不足，同时还配有本人硕士毕业论文中的检测图像以及实验结果，具有一定的参考价值。(CA_CFAR algorithm often requires large computational complexity. OS_CFAR algorithm is presented, which can make up the disadvantages in CA_CFAR. In the meantime, some processed images are given, which has a high value of reference.)

Design Embedded system

外螺旋矩阵的递归和非递归C编程方法 笔试中经常出现的题(Spiral Matrix outside the recursive and non recursive methods written in C programming problems often appear in)

巴特沃斯低通滤波C函数matlab仿真例程(Butterworth low-pass filter C function matlab simulation routines)

simulink，滑模控制的仿真,希望大家学习学习。对新手比较有用(sliding model concord 。)

基于NS模型的超车模型Matlab,用来解决2014美赛建模A题的代码。(Overtaking model based on NS model Matlab.The code used to solve the 2014 Game Modeling A problem.)

5种Swerling目标起伏模型计算检测概率的程序(Probability of Detection Calculation for Detection of Swerling Ⅰ~V Targets)

采用SMI算法的零陷波束形成器，有详细的注解，可更改参数(SMI algorithm using Null Beamformer, detailed comments, can change the parameters)

This utility provides a powerful zooming tool specially designed for the documentation of original and zoomed 2D graphics of images on the same plot. It is composed of two blocks (the secondary axes and the magnifier). The secondary axes, which can be arbitrarily allocated within the limits of the figure, displays the area marked by the magnifier. The highly versatile interface of the on-figure magnifier offers a world of possibilities in a broad range of applications and fields. The Keyboard/mouse or programmatic configuration of this tool allows the user to set her or his own graphic style, to suit the requirements of any publication s editor. More details on interfacing and properties can be found in the .m file.

这是一个基本的数模题目的套路，分析数模聚类问题，例子是乳腺癌的诊断模型，过程为标准化数据，逐步回归，分析主要因素，聚类方法有距离法和神经网络法，均附有源码和解释说明(This is an essential topic of routine digital-analog, digital-analog cluster analysis problem example is the breast cancer diagnostic model, the process for the standardized data, stepwise regression, analysis of major factors, clustering methods from the method and neural network are with source code and explanations)