登录
首页 » matlab » 43-cases-code-for-neural-network-

43-cases-code-for-neural-network-

于 2014-07-08 发布 文件大小:13563KB
0 298
下载积分: 1 下载次数: 113
我要下载

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

下载说明：请别用迅雷下载，失败请重下，重下不扣分！

发表评论

0 个回复

  • Enc_Turbo_3gpp
    this file simulates encoding turbo by using matlab
    2009-02-13 17:48:17下载
    积分：1
  • OSCA-CFAR
    光纤预警系统，基于相位敏感光时域反射计技术的基础上，引入雷达信号系统检测中的OS-CFAR与CA-CFAR相结合方法，对油气管道周围的振动信号进行检测(Optical warning system, based on the phase sensitive optical time domain reflectometer technology, on the basis of the introduction of radar signal in detecting system of OS- CFAR combined with CA- CFAR method, to test the vibration signal of the surrounding oil and gas pipelines )
    2015-04-22 13:54:46下载
    积分：1
  • dingwei
    这是一个很好的车牌定位程序，并且有操作界面，可以逐步操作，非常适合新手(This is a good license plate locator and user interface, step-by-step, very suitable for the novice)
    2012-05-23 11:04:49下载
    积分：1
  • 2
    说明：  modem.qammod对象实现M-QAM调制器，本示例中M为16。其输入参数是从0到15的整数而不是4bits二进制数据。因此，在利用此对象的modulate方法之前需要对二进制数据序列x进行预处理。特别地, 先采用MATLAB中的reshape函数将x沿着矩阵的行方向重新整理成每行4bit数据，然后应用bi2de函数将4bit数据转换成相应的整数。(modem.qammod object implements M-QAM modulator M in this example is 16. Input parameter is an integer from 0 to 15 instead of 4bits binary data. Therefore, before using the method of this object needs to modulate the binary data sequence x pretreatment. In particular, the first use of MATLAB reshape function x 4bit rearranged into each row of data in the row direction of the matrix, and then apply bi2de 4bit function to convert the data into the corresponding integer.)
    2014-09-21 08:29:51下载
    积分：1
  • fourierica
    FourierICA是一种无监管的自适应学习方法，用于盲源分离问题，将短时傅里叶变换STFT与独立分量分析ICA相结合。(FourierICA is an unsupervised learning method suitable for the analysis of bss.The method performs independent component analysis(ICA) on short-time Fourier transforms of the data. )
    2015-01-28 10:49:37下载
    积分：1
  • matlabbook
    说明：  哈工大matlab 讲义 希望对大家有用 对于刚开始学的有作用(HIT matlab useful handouts hope for all of us are just beginning to learn about the role of)
    2008-11-23 16:21:29下载
    积分：1
  • programe123
    程序代码说明 P0201：MATLAB赋值 P0202：MATLAB中的for循环 P0203：MATLAB中的for循环和if条件 P0205：MATLAB图像处理的基本操作 P0206：MATLAB高级图像处理操作 P0207：根据RGB图像创建一幅灰度图像 P0208：二值图像的取反操作 P0209：用imshow函数显示图像 P0210：在同一个窗口内显示两幅图像(code P0201 Note : MATLAB assignment P0202 : MATLAB for the cycle P0203 : MATLAB for the cycle, and if conditions P0205 : MATLAB image processing basic operation P0206 : High MATLAB image processing P0207 : According to RGB images to create a gray-scale image P0208 : binary images from the operation of the anti-P0209 : use imshow function displays images P0210 : in the same window shows two images)
    2007-06-06 15:52:11下载
    积分：1
  • MATLABFUNCTION
    一些常用的MATLAB函数，求和； 求导数； 求极限；求泰勒展开式(Some commonly used MATLAB function, summation order derivative seeking limits order Taylor expansion)
    2009-03-17 17:58:15下载
    积分：1
  • Fast_Fourier_Transform
    快速傅里叶变换 可以计算并且仿真出图片等，里面包括三角变换、逆变换等。(Fast Fourier Transform And simulation can be calculated, such as a picture, which includes the triangular transform, inverse transform and so on.)
    2009-05-20 12:39:05下载
    积分：1
  • Viterbi_Tst
    这是用itpp库编写的卷积码的解码程序。由于用C++库和Intel的MKL库，所以速度飞快。同样的仿真点数， Matlab2012下用了15分半钟，而这个程序仿真只用了半分钟，相当于是matlab速度的30多倍。(This is itpp prepared for the convolutional code decoding process. Because with C++ libraries and Intel' s MKL library, so fast. The same simulation points under Matlab2012 spent 15 and a half minutes, and this program simulation with only half a minute, the equivalent of 30 times the speed of matlab.)
    2014-01-08 14:41:50下载
    积分：1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2026 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！