mvdr

利用matlab实验人脸识别。从图像库中识别出相同人脸。主要运用LDA(Face recognition using matlab experiment. Identified from the image library same faces. The main use of LDA)

标准粒子群算法，应用领域广阔，收敛快计算精度高(Standard particle swarm algorithm, broader applications, fast convergence and high precision )

说明：  趋势EA，不加仓，不网格，每单都带止损止盈，加载周期30分(Trend EA, no warehousing, no grid, stop-loss and stop-profit for each single, loading cycle 30)

本代码为黄华江编著《实用化工计算机模拟—MATLAB在化学工程中的应用》的配套车程序，内容包括该书的所有例子源程序（在Examples目录中）和电子版附录（在名为“附录”的目录中）。(the code Huang Hua Jiang series of "practical computer simulation chemical- MATLAB in chemical engineering application" the matching procedures to The book includes all the examples source (Examples directory) and the electronic version of the Appendix ( "Report "Records of the directory).)

在虚拟仿真环境下进行了几种不同规格零件的抓取试验。在ADAMS中进行仿真试验设置，创建传感器及仿真脚本命令，对两种规格零件进行了抓取试验分析，进一步验证结构设计的正确性及合理性。(the capture of several parts with different specification test was carried out in a virtual simulation environment. To further verify the correctness and the reasonable of the structural design, in ADAMS simulation test, the crawled test and analysis was done for two specifications of parts with the creating of command script and sensor.)

滑膜变结构控制方法的应用例程，争对几个典型系统提供滑膜控制MATLAB程序范例(Variable structure control synovial application routines, for several typical control system synovial sample MATLAB program)

MATLAB is a numeric computation software for engineering and scientific calculations. MATLAB is increasingly being used by students, researchers, practicing engineers and technicians. The causes of MATLAB popularity are legion. Among them are its iterative mode of operation, built-in functions, simple programming, rich set of graphing facilities, possibilities for writing additional functions, and its extensive toolboxes.

比较经典的一个多核学习MKL代码（GMKL Generalized MKL），里面包含其对应的文章，很容易学习和调试！(Learn more classic a multicore MKL Code (GMKL- Generalized MKL), which contains the corresponding article, it is easy to learn and debug!)

本源码用MATLAB语言实现了自适应RLS算法，并附有FFT分析(rls fft)

time domain symptom extraction