FM_phase_noise_1

宝典丛书的一本，很新的，matlab图像处理与界面编程的课后源程序。有很好的学习价值(A book series, it is new, matlab image processing and after-school programming source interface. Learning the value of good)

music算法程序，基本MUSIC算法仿真程序，进行DOA估计(MUSIC algorithm)

逻辑双闭环控制仿真电路，可以帮助分析直流电机拖动系统控制设计。(failed to translate)

Jerk混沌系统产生的模拟信号的均值化处理 方法简单效果明显(Mean treatment method Jerk chaotic system to produce an analog signal simple obvious effect)

滞环电流模块，可用于伺服电机来仿真使用，效果很好！(Hysteresis current module can be used to simulate the use of servo motors, the effect is very good!)

与Field_II配套使用，提供了一个基于matlab平台的gui界面，可自由定制参数，选择成像方式，功能强大。(This tutorial is designed to give you an introduction to Field_II, an acoustic pressure field simulation package written by Dr. Joergen Jensen. is the method for you. To run this tutorial, you will need to have MATLAB available on your computer. Download the Field_II source code and the Field_II_GUI files to your machine,and then run through the tutorial.)

波束形成，多信号的信号谱估计，基于线性约束最小方差准则(Beamforming, signal spectrum multiple signal estimates based linearly constrained minimum variance criterion)

说明：  线性约束下基于LQR方法的车辆路径跟踪，用于无人驾驶。(Vehicle path tracking based on LQR method under linear constraints is used for unmanned driving.)

平面桁架程序，主要针对土木工程设计计算领域，给出了计算数据，及计算程序，值得学习(Plane truss procedures, mainly for the field of civil engineering design calculations are given calculated data, and calculation procedures, it is worth learning)

说明：  SGA（Simple Genetic Algorithm）是一种强大的智能多变量优化算法，它模仿种群繁殖规律来进行优化。本SGA可以优化变量，求最小值,最大值（当把函数倒数也就求最小值） 并且支持浮点编码，grey编码，二进制编码；轮赌法选择，锦标赛选择；单点交叉，均布交叉，浮点交叉；单点变异，浮点变异；调用时Genetic（目标函数名） 使用SGA时，首先需要一个目标函数（像AimFunc.m），该函数返回适应度输入变量为待优化变量x输出为一个适应度。然后修改Genetic.m中可以修改的地方(SGA (Simple Genetic Algorithm) is a powerful smart multi-variable optimization algorithm, which mimics the reproduction of law to be optimized. The SGA can be optimized variables, minimum, maximum, (when the function will last for the minimum) and supports the floating-point encoding, grey code, binary code round of betting method selection, tournament selection single-point crossover, uniform crossover , floating-point crossover single point mutation, floating-point mutation called Genetic (objective function name) the use of SGA, first of all need an objective function (like AimFunc.m), the fitness function returns the input variables to be optimized for the output variable x a fitness. Can be modified and then modify the place Genetic.m)