SplashScreen

说明：  介绍了几个用于弱信号捕获的不同的信号处理方法，并对其捕获性能进行了比较。(A number of differential signal processing schemes have been proposed to address weak signal processing.)

这个程序是基于混合高斯背景模型的运动目标检测算法，m文件和所用视频放到matlab的工作目录下即可运行(This program is based on the Gaussian mixture background model of moving target detection algorithm, m, and used video files into matlab working directory to run)

Y.T.Chan在其论文中提出一种具有解析表达式解的非递归双曲线方程组解法，该算法具有计算量小，速度快，且当TDOA参数估计误差服从高斯分布的情况下，定位精度较高。 本程序借鉴Chan论文中提出的算法，基于MATLAB程序，在已知TDOA估计参数的情况下，对信号源位置进行估计。 希望能够对研究 干扰源定位、无源定位的同志提供帮助。(YTChan in his paper presents a solution with the analytical expression for the non-recursive solution of hyperbolic equations, the algorithm has calculated the amount of small, fast, and when the TDOA estimation error of Gaussian distribution in the case, positioning accuracy than high. The papers presented in the program learn from Chan algorithm, MATLAB-based program, known TDOA estimation parameters in the case, the signal source location estimates. Hope to the study of interference location, passive positioning of the comrades to help.)

DOA MUSIC for array antenna

MATLAB空时分组码仿真，用于检测编码性能(MATLAB simulation of space-time block codes for the detection of coding performance)

续common rail system simulink 1内容，柴油机高压共轨系统simlink程序，含高压油泵、共轨管、喷油器等，喜欢的朋友请多多支持(Continued common rail system simulink 1 content Diesel Common Rail the system simlink program, with high pressure fuel pump, common rail, injector, etc., like a friend to a lot of support)

This derivation of the normalised least mean square algorithm is based on Farhang- Boroujeny 1999, pp.172-175, and Diniz 1997, pp 150-3. To derive the NLMS algorithm we consider the standard LMS recursion, for which we select a variable step size parameter, μ(n). This parameter is selected so that the error value , e+(n), will be

支持向量机点点滴滴matlab版，内容不错较为新颖 有很强的实用价值(More novel support vector machine bit by bit matlab version has a strong practical value)

Quantum Particle Swarm Optimization matlab

matlab程序，自动多阈值分割，本方法较好用适合，经本人亲自验证(matlab program, automatic multi-threshold segmentation, the method used for good, I personally verified by the)