mat

This is a version of Foschini-Miljanic, an itarative algoriyhm for power control in wireless computer networks.

MATLAB图像处理的教程，常用的一些函数(MATLAB Image Processing tutorial, used some of the functions)

说明：  智能控制 模糊控制 神经网络控制序号 多变量控制系统设计(Intelligent control fuzzy control of multivariable control system design of the neural network control of serial number)

MATLAB的GUI教程,GUI的基本说明与操作以及部分实例,内容为英文(MATLAB GUI guides, a basic description of the GUI and operating, and some examples, says English)

程序实例，以简洁高效的代码来实现许多程序的功能，是初学者快速入门的经典教材。(procedures matlab examples, concise and efficient code to achieve a number of procedures and functions, are beginners QuickStart classic materials.)

线性四叉树编码，包括四进制和十进制数据的编码(Linear quadtree coding, including four hexadecimal and decimal data coding)

非常好的向前和向后插值两种方法：用matlab实现最近邻域插值旋转程序(very good ，ifyou want please loadown)

层次分析法，直接可以用的matlab程序，包含两个文件(AHP)

训练集/测试集产生 load spectra_data.mat 随机产生训练集和测试集 temp = randperm(size(NIR,1)) 训练集——50个样本 P_train = NIR(temp(1:50),:) T_train = octane(temp(1:50),:) 测试集——10个样本 P_test = NIR(temp(51:end),:) T_test = octane(temp(51:end),:) N = size(P_test,2) 数据归一化 ( Training set/test set generation load spectra_data.mat randomly generated training set and test set temp = randperm (size (NIR, 1)) training set- 50 samples P_train = NIR (temp (1:50) ,:)' T_train = octane (temp (1:50 ),:)' test set- 10 samples P_test = NIR (temp (51: end ),:)' T_test = octane (temp (51 : end ),:)' N = size (P_test, 2) Data Normalization)

基于二阶泛模型的无模型自适应控制及参数整定，充分利用无模型自适应控制边建模边控制的特点，推导基于二阶泛模型的改进无模型自适应控制，应用辨识出的近似模型针对不同目标函数进行优化(Pan model based on second order approximation model of model-free adaptive control and parameter tuning, make full use of model-free adaptive control side edge control modeling features derived model-free adaptive control model based on improved second-order pan, identify the application The objective function to be optimized for different)