matlab-functions-command-

capacity of multi input multi output

SIMULINK实现QAM,来自韩国一本教材。(SIMULINK realize QAM, a teaching materials from South Korea.)

几个简单的matlab实例，新手学习matlab可用(A few simple matlab example, matlab novice can learn)

It introduces how to work with MATLAB

一个关于TV模型算法的编写程序代码 具有很好的去除噪声效果(A about TV model algorithm of writing code has the very good for removing noise effect)

基于MATLAB用于检测提取的语音信号的平均短时过零率的算法，可以方便的检测出是清音还是浊音。(Algorithm based on the MATLAB for detecting extracted speech signal average short-term zero-crossing rate, you can easily detect the voiceless or voiced.)

可用於arima的計算,檢測數據以及預測用途(do arima)

matlab 基础教程的课件 ，第二章，对初学者有一定作用。(matlab Essentials courseware, and the second chapter, there is a role for beginners.)

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.)

image splitting by using k means clustering algorithm