Dual-simplex

说明：  用matlab实现的区域生长算法,易懂，对于初学者很有参考价值(the regiongrowing algorithm using MATLAB)

多个电力电子、电机仿真模型。是重要的学习电力电子simulink 仿真的素材，权威教材，内容较多，分成上下两集,这个是上(useful simulink modles for leaners)

经典教材2012最新版Introduction to Random Signals and Applied Kalman Filtering,4thedition，配套例程(2012 the latest edition of the classic textbook Introduction to Random Signals and Applied Kalman Filtering, 4thedition, supporting routine)

The objective is to illustrate the coordinated sampling of a geometrical shape such as an eclipse is used in this case. For illustrative purposes the gridded plot is sampled by detection of line beam intersections of the edge and in-bound regions of the eclipse. The coordinates are traced and pixelized into an image map.

Matlab实现界面友好，利用matlab针对图像进行马氏距离计算 ,抑制载波型差分相位调制。( Matlab to achieve user-friendly, Using matlab to calculate the Mahalanobis distance for the image, Suppressed carrier type differential phase modulation.)

说明：  用于数值计算中的三次样条插值函数方法，基于matlab编写(spline interpolation)

基于双树小波通用隐马尔可夫树模型的图像压缩感知(Compressive Sensing for Image Using Orthogonal Wavelet Transform and Orthogonal Matching Pursuit Algorithm)

说明：  采用BP神经网络算法进行调制样式识别的Matlab代码(Using BP neural network pattern recognition algorithm Matlab code modulation)

此程序把M序列作为输入，使用最小二乘法对系统进行辨识，实现最小二乘的基本功能(M sequences in this program as input, using the least squares method to identify the basic functions of the least squares)

《MATLAB控制系统仿真与实例详解》一书的光盘源码。图书简介：本书详细地讲解了MATLAB 7.x的功能与相关操作以及MATLAB在控制系统中的仿真应用。本书内容包括控制系统仿真基础、MATLAB程序设计语言基础、控制系统理论基础、Simulink交互式仿真环境、控制系统建模、线性控制系统的分析与仿真、PID控制系统设计及仿真、最优控制系统设计、鲁棒控制系统设计、神经网络系统设计及其MATLAB实现、模糊控制系统设计和系统辨识。 (" MATLAB Control System Simulation and explain examples of" one-source book on CD-ROM. Book Description: This book explain in detail the function of the MATLAB 7.x and related operations and MATLAB in the control system simulation applications. The book includes basic control system simulation, MATLAB programming language basic, basic control system theory, Simulink interactive simulation environment, control system modeling, linear control system analysis and simulation, PID control system design and simulation, optimal control system design, robust control system design, neural network system design and MATLAB implementation, fuzzy control system design and system identification.)