ABCTFR

求解平面势流下的圆柱绕流问题，基于MATLAB的有限元法编程。(cylinder，finite elements method)

数字图像处理程序，完成卡尼边缘检测数字图像处理算法可对数字图像实现边缘检测(Digital image processing program, complete Carney digital image processing algorithm for edge detection can be achieved on the digital image edge detection)

采用matlab实现的wsn节点算法，对于研究wsn非常有好处。虽然有很多人有类似的代码，但是这个代码比较相信。(Using matlab to achieve wsn node algorithm for the study of wsn very good. Although many people have similar code, but this code is to believe.)

matlab 蜂群算法工具箱，简单快速的解决TSP问题(matlab )

说明：  该程序是基于MATLAB的磁悬浮控制系统的离散控制算法实现程序(The program is based on discrete control algorithm based on MATLAB magnetic levitation control system to achieve program)

OPTIMAL BEAMFORMING MIMO MASSIVE

本书分为三部分。第一部分介绍MATLAB面向对象编程基础知识，包括什么是类，类之间的基本关系，以及MATLAB提供的面向对象编程语言的具体功能；第二部分是面向对象编程的进阶篇，对概念进行归类，方面读者在编程中遇到问题时查询和检索；第三部分把面向对象编程的方法应用到实际问题中，并且从实际问题中抽象出一般的解决方法，即为设计模式。 本书可作为高等院校本科师生、研究生MATLAB课程的辅助读物，也可以作为从事科学计算、程序设计的科研人员的参考书。(This book is divided into three parts. The first part introduces the basic knowledge of object-oriented programming in MATLAB, including what is the class, the basic relationship between classes, and the specific functions of object-oriented programming language provided by MATLAB; the second part is the advanced part of object-oriented programming, which classifies the concepts and queries and retrieves when the readers encounter problems in programming. In the third part, the object-oriented programming method is applied to the actual problems, and the general solution is abstracted from the actual problems, that is, the design pattern. This book can be used as an auxiliary reading material for undergraduate teachers, students and graduate students in MATLAB course, and also as a reference book for scientific researchers engaged in scientific calculation and programming.)

说明：  matlab编程教程，matlab宝典是全面的查阅文献，供编程时按索引查找学习。(reference of matlab coding)

a neural network - GA toolbo for intelligent control

x0 = ones(2,2) Make a starting guess at the solution options = optimset( Display , off ) Turn off Display [x,Fval,exitflag] = fsolve(@myfun,x0,options) The solution is x = -0.1291 0.8602 1.2903 1.1612 Fval = 1.0e-009 * -0.1619 0.0776 0.1161 -0.0469 exitflag = 1 and the residual is close to zero. sum(sum(Fval.*Fval)) ans = 4.7915e-020