kalman

利用VC++6.0集成编程界面编写综合运用MAT数据文件和MATLAB引擎技术的（求矩阵的奇异值）C++源码程序。本程序说明了：1.如何利用VC++6.0集成编程界面编写源码程序；2.编译链接产生EXE文件所需的间夹文件。注意：要将压缩包内除matlabyinqingwithc++.cpp的所有文件都要拷贝到matlabyinqingwithc++.cpp的“任务文件夹下”。(Use VC++ 6.0 integrated programming interface MAT preparation of comprehensive use of data files and MATLAB engine technology (the singular value matrix) C++ Source procedures. This procedure describes: 1. How to use VC++ 6.0 integrated programming interface to prepare source procedures 2. Compiler generated EXE file the necessary link between the document folder. NOTE: In addition to compression packages matlabyinqingwithc++. Cpp must copy all the files to matlabyinqingwithc++. Cpp s mission folder. )

中心显示格式求解poisson方程以及在平均值型误差下误差值，矩形区域，狄利克雷边界情况！(Center the display format for solving poisson equation in the average error under the error type, rectangular area, Dirichlet boundary conditions!)

turbo simulation with the use of functions part 1

Pattern Recognition file to read the letter or the numbers so we can recognize it

这里上传混沌电路导论的第一章的仿真，包括：chen、Henon、Augmentation_lv、Logistic、Rossler、Lv系统的相轨图等，适合混沌入门的学生使用(Here the first chapter of the introduction of chaos circuit simulation, including: Chen, Henon, Augmentation_lv, Logistic, Rossler, Lv system, such as the phase diagram, suitable for the use of the chaos of the students)

Theoretical gravity anomaly of fault model and generation of Gaussian random noise

自适应滤波器，求解性能误差曲面和等值曲线，最陡下降法和LMS算法的比较，(Adaptive filter, the solution surface and contour error performance curve, the steepest descent method and the LMS algorithm,)

Hybrid Particle Swarm Optimation Algorithm. This file is helpful someone who want to optimatize data.

数据模型归一化，模态振动，采用的是脉冲对消法，含噪脉冲信号进行相关检测,分析了该信号的时域、频域、倒谱，循环谱等,使用起来非常方便。( Normalized data model, modal vibration, It uses a pulse of consumer law, Noisy pulse correlation detection signal, Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. Very convenient to use.)

This toolbox was written for my own education and to give me a chance to explore the models a bit. It is NOT intended for any serious applications and it does not NOT do many of things you would want a mature implementation to do, like leaf pruning. If you wish to use a strong implementation I recommend Scikit Learn / Python. For Matlab I do not really have a recommendation.