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多变量输入、输出、多干扰、非线性和强耦合的复杂系统控制是一个比较困难的问题，常用的控制器可能因为多变量耦合问题难以控制系统。PID神经元网络是一种多层前向神经元网络，它的各层神经元个数、连接方式、连接权值是按照PID控制规律的已有原则和经验确定的，是一种动态的符合控制系统的前向网络。但是由于PID网络初始权值随机取值的原因，每次控制的效果都有所差别，个别情况下控制效果还比较差。本案例研究了基于PID神经元的多变量耦合系统控制，并用PSO算法来优化控制器以取得更好的控制效果。(Multivariable input, output, and more interference, complex nonlinear and strong coupling system control is a more difficult problem, commonly used multivariable controller may be because the problem is difficult to control the coupling system. PID neural network is a multi-front to neural networks, its number of neurons in each layer, connection, connection weights are in accordance with the existing principles and experience to determine the PID control law is a dynamic compliance before the control system to the network. However, due to the random initial weights of the network PID values ​ ​ of reason, every time there are differences in the effect of control and in some cases the control effect is still relatively poor. This case study of multivariable coupling system based on PID control neurons, and with PSO algorithm to optimize the controller to achieve better control effect.)

本文档主要介绍matlab神经网络的工具箱的开发实例和函数调用(This document introduces the matlab neural network toolbox development examples and function call)

使用matlab实现包络检波，调制解调。很好的画出包络信号。(Use matlab realize envelope detector, modulation and demodulation. Good draw envelope signal.)

四种脉压信号仿真，包括线性调频，巴克码，简单的混沌，和HFM(Four kinds of pulse pressure signal simulation)

说明：  将GPS得到的经纬度，大地坐标，通过高斯投影正算，得到平面直角坐标 文件大小不够，再增加了高斯投影的pdf文档(The longitude, latitude and geodetic coordinates obtained by GPS are corrected by Gauss projection, and the plane rectangular coordinates are obtained.)

光通信中非归零型差分相位调制信号建模与仿真分析(Optical Communication Central African zero differential phase modulated signal-based modeling and simulation analysis)

pattern classification, second edition, 中文版(pattern classification, second edition, chinese version)

用matab实现离散信号a(n)和b(n)的线性卷积和圆周时域卷积，并显示。(A discrete signal with matab a (n) and b (n) linear time-domain convolution and circular convolution, and display.)

说明：  模型预测算法，传递函数对象为例，程序以及仿真曲线(MPC.model predict.transfromation.)

induction motor servo drive