43-cases-code-for-neural-network-
代码说明:
该压缩包中有史峰等人编写的《MATLAB神经网络43个案例分析》的全部代码及数据。对于MATLAB的初学者很有帮助。(The archive has written the history of Feng et al "MATLAB neural network 43 case studies" of all the code and data. MATLAB is helpful for beginners.)
文件列表:
《MATLAB 神经网络43个案例分析》源代码&数据
..........................................\《MATLAB 神经网络43个案例分析》目录.docx,176168,2013-08-20
..........................................\第10章 离散Hopfield神经网络的分类——高校科研能力评价
..........................................\.....................................................\chapter10.m,1452,2013-09-02
..........................................\.....................................................\class.mat,443,2009-10-06
..........................................\.....................................................\Readme.txt,453,2013-09-02
..........................................\.....................................................\sim.mat,465,2009-10-06
..........................................\.....................................................\stdlib.m,249,2013-09-02
..........................................\.....................................................\test.m,807,2013-09-02
..........................................\第11章 连续Hopfield神经网络的优化——旅行商问题优化计算
..........................................\.......................................................\city_location.mat,232,2009-09-21
..........................................\.......................................................\diff_u.m,217,2009-12-21
..........................................\.......................................................\energy.m,247,2010-01-30
..........................................\.......................................................\main.m,2674,2013-09-02
..........................................\.......................................................\Readme.txt,434,2013-09-02
..........................................\第12章 初始SVM分类与回归
..........................................\........................\Chapter_ClassifyRegressUsingLibsvm.m,2555,2013-08-18
..........................................\........................\heart_scale.mat,28904,2005-03-22
..........................................\........................\html
..........................................\........................\....\Chapter_ClassifyRegressUsingLibsvm.html,14895,2013-08-18
..........................................\第13章 LIBSVM参数实例详解
..........................................\.........................\Chapter_ModelDecryption.m,1308,2013-08-18
..........................................\.........................\heart_scale.mat,28904,2005-03-22
..........................................\.........................\html
..........................................\.........................\....\Chapter_ModelDecryption.html,8933,2013-08-18
..........................................\第14章 基于SVM的数据分类预测——意大利葡萄酒种类识别
..........................................\....................................................\chapter_WineClass.m,2429,2013-08-18
..........................................\....................................................\chapter_WineClass.mat,20168,2010-01-30
..........................................\....................................................\html
..........................................\....................................................\....\chapter_WineClass.html,13636,2013-08-18
..........................................\第15章 SVM的参数优化——如何更好的提升分类器的性能
..........................................\..................................................\chapter_GA.m,6450,2013-08-18
..........................................\..................................................\chapter_GridSearch.m,6042,2013-08-18
..........................................\..................................................\chapter_PSO.m,8453,2013-08-18
..........................................\..................................................\html
..........................................\..................................................\....\chapter_GA.html,25844,2013-08-18
..........................................\..................................................\....\chapter_GridSearch.html,25305,2013-08-18
..........................................\..................................................\....\chapter_GridSearch.png,3346,2013-08-18
..........................................\..................................................\....\chapter_GridSearch_01.png,6819,2013-08-18
..........................................\..................................................\....\chapter_GridSearch_02.png,10865,2013-08-18
..........................................\..................................................\....\chapter_GridSearch_03.png,12638,2013-08-18
..........................................\..................................................\....\chapter_GridSearch_04.png,16328,2013-08-18
..........................................\..................................................\....\chapter_GridSearch_05.png,21970,2013-08-18
..........................................\..................................................\....\chapter_GridSearch_06.png,15673,2013-08-18
..........................................\..................................................\....\chapter_GridSearch_07.png,9098,2013-08-18
..........................................\..................................................\....\chapter_PSO.html,32779,2013-08-18
..........................................\..................................................\....\chapter_PSO.png,3330,2013-08-18
..........................................\..................................................\....\chapter_PSO_01.png,6819,2013-08-18
..........................................\..................................................\....\chapter_PSO_02.png,10865,2013-08-18
..........................................\..................................................\....\chapter_PSO_03.png,13951,2013-08-18
..........................................\..................................................\....\chapter_PSO_04.png,9095,2013-08-18
..........................................\..................................................\wine.mat,20168,2010-01-30
..........................................\第16章 基于SVM的回归预测分析——上证指数开盘指数预测
..........................................\....................................................\chapter_sh.m,5527,2013-10-19
..........................................\....................................................\chapter_sh.mat,219976,2010-01-30
..........................................\....................................................\html
..........................................\....................................................\....\chapter_sh.html,24872,2013-08-18
..........................................\....................................................\....\chapter_sh_05.png,22389,2013-08-18
..........................................\....................................................\....\chapter_sh_06.png,17509,2013-08-18
..........................................\....................................................\....\chapter_sh_07.png,12441,2013-08-18
..........................................\....................................................\....\chapter_sh_08.png,12113,2013-08-18
..........................................\....................................................\....\chapter_sh_09.png,10681,2013-08-18
..........................................\第17章 基于SVM的信息粒化时序回归预测——上证指数开盘指数变化趋势和变化空间预测
..........................................\..............................................................................\chapter_FIGsh.m,9772,2013-08-18
..........................................\..............................................................................\chapter_sh.mat,256680,2010-01-30
..........................................\..............................................................................\FIG_D.m,6456,2009-03-21
..........................................\..............................................................................\html
..........................................\..............................................................................\....\chapter_FIGsh.html,41176,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_05.png,24304,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_06.png,12990,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_07.png,13284,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_08.png,11396,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_09.png,17434,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_10.png,23764,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_11.png,12273,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_12.png,14398,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_13.png,11684,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_14.png,16538,2013-08-18
..........................................\..............................................................................\....\chapter_FIGsh_15.png,21487,2013-08-18
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