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现代谱估计的ESPRIT、Music算法仿真(Modern Spectral Estimation ESPRIT, Music algorithm simulation)

一个RBF神经网络的算法实现程序,可用于实现RBF神经网络的函数逼近(A RBF neural network algorithm procedure can be used to implement RBF neural network function approximation)

分数阶传递函数的类描述，绘制bode图、nyquist图(fractional order system， bode )

NSGA2算法中文版详细介绍,非常实用的多目标优化代码(NSGA2 algorithm Chinese version in detail)

FFH中传统门限的比较获取，SNR的不同，BER不同，从中最佳(FFH traditional door limit access to the SNR different BER, from which the best)

卡尔曼滤波器是一个对动态系统的状态序列进行线性最小误差估计的算法，一般用于线性系统。一般在运动跟踪领域中摄像机相对于目标物体运动有时属于非线性系统，但由于在一般运动跟踪问题中图像采集时间间隔较短，可近似将单位时间内目标在图像中的运动看作匀速运动，采用卡尔曼滤波器可以实现对目标运动参数的估计。(Kalman filter is a state sequence of linear dynamic systems smallest error estimation algorithm for linear systems in general. Usually in the field of motion tracking camera motion with respect to the target object may belong to nonlinear systems, but in general due to motion tracking problems shorter image acquisition time interval, a unit of time can be approximated to the target motion in the image is regarded as uniform motion, Kalman filter can achieve the target motion parameter estimation.)

说明：  该系统为基于MATLAB平台的PCA的人脸识别系统，可识别ORL和YALE人脸库，方法实现统一，包括GUI界面。另外可二次开发成摄像头的实时人脸系统，识别出库外人脸，可做成门禁系统，考勤系统，打卡签到系统。实现登记出勤，报警等。 含论文，详细注释。(The system is a PCA face recognition system based on MATLAB platform. It can recognize ORL and yale face database. The method is unified, including GUI interface. In addition, it can be developed into a real-time face system of camera, which can recognize the face outside the warehouse, and can be made into access control system, attendance system, punch in system. Register attendance, alarm, etc. Including paper and detailed notes.)

a book about wifi. very informative

读取图片，图片格式转换，并对二值图像进行投影角度分别为0、25的radon变换，显示结果(Read the picture, the picture format conversion, and binary image projection angle of radon transform 0,25 respectively, results)

The optimization behavior of the self-adaptation (SA) evolution strategy (ES) with intermediate multirecombination (the (=I )-SA-ES) using isotropic mutations is investigated on the general elliptic objective function. An asymptotically exact quadratic progress rate formula is derived. This is used to model the dynamical ES system by a set of difference equations. The solutions of this system are used to analytically calculate the optimal learning parameter  . The theoretical results are compared and validated by comparison with real (=I )-SA-ES runs on typical elliptic test model cases. The theoretical results clearly indicate that using a model-independent learning parameter  leads to suboptimal performance of the (=I )-SA-ES on objective functions with changing local condition numbers as often encountered in practical problems with complex fitness landscapes.