LinearShootingMethod

这里是一些VC与matlab混合编程的最新技术资料。有些是介绍了在VC ++调用Matlab的常用方法及各自特点，还有一些是介绍VC与matlab混合编程的实例。(Here are some VC mixed with matlab programming information on the latest technologies. Some are introduced in VC++ calling Matlab common methods and their own characteristics, and some is to introduce the VC with the matlab programming examples of mixing.)

analogique simulation matlab de pll

这是进行小波边缘检测的程序，用matlab编程，小波比其他算子具有一定的优势。(This is the wavelet edge detection procedure, using matlab programming, wavelet than other operators have certain advantages.)

遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。(Genetic Algorithm (Genetic Algorithm) is a simulation of natural selection and genetics of Darwinian biological evolution computational models of biological evolution, the process is a way to search the optimal solution by simulating the natural evolution.)

说明：  Leader Selection for optimization algorithms

对二维和三维数据可视化,图像处理,动画制作等高层次的绘图命令,也包括可以修改图形及编制完整图形界面的,低层次的绘图命令(Of two-dimensional and three-dimensional data visualization, image processing, high-level animation of graphics commands, but also can modify the graphics and the preparation of a full graphical interface, and low-level graphics command)

实现加减乘除sqr和abs函数的任意整型和浮点型运算(Addition and subtraction and multiplication and division to achieve abs function sqr arbitrary integer and floating-point operations)

关于功率谱估计的论文，论文里面写有程序的，包括，窗函数方法，多窗估计法，自相关算法AR模型谱估计。(A paper on the power spectrum estimation, the paper inside to write a program, including, window function method, multi-window estimation, autocorrelation AR model spectrum estimation algorithm.)

基于知识的恒虚警检测——KB-CFAR检测器：包括对于无目标、仅有噪声的信号进行KB-CFAR检测的仿真，以及对于含目标、且在瑞利杂波背景下的KB算法仿真。一些程序主要是为了绘图，画出KB-CFAR检测过程中的信号波形以及检测门限对比图；而另一些程序是为了计算KB-CFAR检测过程中的检测概率和虚警概率。(KB-CFAR detectors: simulations of detection to signals with no target but noise only, as well as signals with target and the background of Rayleigh clutter. Some programs are aimed at giving pictures of the signals and detectiong threshold in the process of detection using KB-CFAR algorithm, while other programs are aimed at calculating the detecting rate and false alarm rate of KB-CFAR algorithm.)

本文应用SMQT和 SPLIT UP SNOW 分类器来完成对人脸的检测。(The purpose of this paper is threefold: firstly, the local Successive Mean Quantization Transform features are proposed for illumination and sensor insensitive operation in object recognition. Secondly, a split up Sparse Network of Winnows is presented to speed up the original classifier. Finally, the features and classifier are combined for the task of frontal face detection. Detection results are presented for the MIT+CMU and the BioID databases. With regard to this face detector, the Receiver Operation Characteristics curve for the BioID database yields the best published result. The result for the CMU+MIT database is comparable to state-of-the-art face detectors.)