MATLAB code The first chapter is BP neural network data classification -- speech characteristic signal classification The second chapter is the nonlinear system modeling of BP neural network nonlinear function fitting The third chapter, genetic algorithm optimization BP neural network - nonlinear function fitting The fourth chapter, neural network, genetic algorithm, function extreme value optimization nonlinear function extremum seeking The fifth chapter is based on BP_Adaboost's strong classifier design -- the company financial early-warning model The sixth chapter is PID neural network decoupling control algorithm multivariable system control The seventh chapter is the regression of RBF network the realization of nonlinear function regression .........the last is 58 chapters

Filename	Size	Update
代码
代码\44层次分析
代码\44层次分析\CENCI2.m
代码\45灰色关联度度
代码\45灰色关联度度\huiseguanliand1.m
代码\46熵权法
代码\46熵权法\sqf.m
代码\47主成分分析
代码\47主成分分析\pca.m
代码\48主成分回归
代码\48主成分回归\PCR_Demo.m
代码\49偏最小二乘回归
代码\49偏最小二乘回归\PLS.m
代码\50逐步回归
代码\50逐步回归\stepwise.zip
代码\51模拟退火
代码\51模拟退火\SA_GUI_Demo
代码\51模拟退火\SA_GUI_Demo\fitness.m
代码\51模拟退火\SA_GUI_Demo\html
代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo.html
代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo.png
代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_01.png
代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_02.png
代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_03.png
代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_04.png
代码\51模拟退火\SA_GUI_Demo\html\SA_GUI_demo_05.png
代码\51模拟退火\SA_GUI_Demo\main.m
代码\51模拟退火\SA_TSP_Demo
代码\51模拟退火\SA_TSP_Demo\Distance.m
代码\51模拟退火\SA_TSP_Demo\DrawPath.m
代码\51模拟退火\SA_TSP_Demo\Metropolis.m
代码\51模拟退火\SA_TSP_Demo\NewAnswer.m
代码\51模拟退火\SA_TSP_Demo\OutputPath.m
代码\51模拟退火\SA_TSP_Demo\PathLength.m
代码\51模拟退火\SA_TSP_Demo\html
代码\51模拟退火\SA_TSP_Demo\html\main.html
代码\51模拟退火\SA_TSP_Demo\html\main.png
代码\51模拟退火\SA_TSP_Demo\html\main_01.png
代码\51模拟退火\SA_TSP_Demo\html\main_02.png
代码\51模拟退火\SA_TSP_Demo\html\main_03.png
代码\51模拟退火\SA_TSP_Demo\main.m
代码\52RBF	GRNN	PNN-神经网络
代码\52RBF	GRNN	PNN-神经网络\ClassCode
代码\52RBF	GRNN	PNN-神经网络\ClassCode\html
代码\52RBF	GRNN	PNN-神经网络\ClassCode\html\main_GRNN_PNN.html
代码\52RBF	GRNN	PNN-神经网络\ClassCode\html\main_GRNN_PNN.png
代码\52RBF	GRNN	PNN-神经网络\ClassCode\html\main_GRNN_PNN_01.png
代码\52RBF	GRNN	PNN-神经网络\ClassCode\html\main_GRNN_PNN_02.png
代码\52RBF	GRNN	PNN-神经网络\ClassCode\html\main_GRNN_PNN_03.png
代码\52RBF	GRNN	PNN-神经网络\ClassCode\html\main_RBF.html
代码\52RBF	GRNN	PNN-神经网络\ClassCode\html\main_RBF.png
代码\52RBF	GRNN	PNN-神经网络\ClassCode\html\main_RBF_01.png
代码\52RBF	GRNN	PNN-神经网络\ClassCode\iris_data.mat
代码\52RBF	GRNN	PNN-神经网络\ClassCode\main_GRNN_PNN.m
代码\52RBF	GRNN	PNN-神经网络\ClassCode\main_RBF.m
代码\52RBF	GRNN	PNN-神经网络\ClassCode\spectra_data.mat
代码\53 竞争神经网络与SOM神经网络
代码\53 竞争神经网络与SOM神经网络\ClassCode.rar
代码\54蚁群算法tsp求解
代码\54蚁群算法tsp求解\citys_data.mat
代码\54蚁群算法tsp求解\html
代码\54蚁群算法tsp求解\html\main.html
代码\54蚁群算法tsp求解\html\main.png
代码\54蚁群算法tsp求解\html\main_01.png
代码\54蚁群算法tsp求解\html\main_02.png
代码\54蚁群算法tsp求解\main.m
代码\55灰色预测
代码\55灰色预测\gm1_1benrentest.m
代码\56 模糊综合评价
代码\56 模糊综合评价\27194323mohu.rar
代码\58曲线拟合
代码\58曲线拟合\myfun.m
代码\58曲线拟合\nihe.m
代码\58曲线拟合\拟合图.png
代码\chapter1
代码\chapter1\BPDLX.m
代码\chapter1\chapter1_1.asv
代码\chapter1\chapter1_1.m
代码\chapter1\data1.mat
代码\chapter1\data2.mat
代码\chapter1\data3.mat
代码\chapter1\data4.mat
代码\chapter10
代码\chapter10\Readme.txt
代码\chapter10\chapter10.m
代码\chapter10\class.mat
代码\chapter10\sim.mat
代码\chapter10\stdlib.m
代码\chapter10\test.m
代码\chapter11
代码\chapter11\Readme.txt
代码\chapter11\city_location.mat
代码\chapter11\diff_u.m
代码\chapter11\energy.m
代码\chapter11\main.m
代码\chapter12
代码\chapter12\Chapter_ClassifyRegressUsingLibsvm.m
代码\chapter12\heart_scale.mat
代码\chapter12\html
代码\chapter12\html\Chapter_ClassifyRegressUsingLibsvm.html

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