登录
首页 » matlab » DeepLearnToolbox-master

DeepLearnToolbox-master

于 2020-06-19 发布
0 158
下载积分: 1 下载次数: 11

代码说明:

说明:  CNN,DBN算法可以对手写体数字进行识别,准确率高(CNN and DBN algorithm can recognize handwritten numerals with high accuracy)

文件列表:

DeepLearnToolbox-master, 0 , 2014-01-12
DeepLearnToolbox-master\.travis.yml, 249 , 2014-01-12
DeepLearnToolbox-master\CAE, 0 , 2014-01-12
DeepLearnToolbox-master\CAE\caeapplygrads.m, 1219 , 2014-01-12
DeepLearnToolbox-master\CAE\caebbp.m, 917 , 2014-01-12
DeepLearnToolbox-master\CAE\caebp.m, 1011 , 2014-01-12
DeepLearnToolbox-master\CAE\caedown.m, 259 , 2014-01-12
DeepLearnToolbox-master\CAE\caeexamples.m, 754 , 2014-01-12
DeepLearnToolbox-master\CAE\caenumgradcheck.m, 3618 , 2014-01-12
DeepLearnToolbox-master\CAE\caesdlm.m, 845 , 2014-01-12
DeepLearnToolbox-master\CAE\caetrain.m, 1148 , 2014-01-12
DeepLearnToolbox-master\CAE\caeup.m, 489 , 2014-01-12
DeepLearnToolbox-master\CAE\max3d.m, 173 , 2014-01-12
DeepLearnToolbox-master\CAE\scaesetup.m, 1937 , 2014-01-12
DeepLearnToolbox-master\CAE\scaetrain.m, 270 , 2014-01-12
DeepLearnToolbox-master\CNN, 0 , 2014-01-12
DeepLearnToolbox-master\CNN\cnnapplygrads.m, 575 , 2014-01-12
DeepLearnToolbox-master\CNN\cnnbp.m, 2141 , 2014-01-12
DeepLearnToolbox-master\CNN\cnnff.m, 1774 , 2014-01-12
DeepLearnToolbox-master\CNN\cnnnumgradcheck.m, 3430 , 2014-01-12
DeepLearnToolbox-master\CNN\cnnsetup.m, 2020 , 2014-01-12
DeepLearnToolbox-master\CNN\cnntest.m, 193 , 2014-01-12
DeepLearnToolbox-master\CNN\cnntrain.m, 845 , 2014-01-12
DeepLearnToolbox-master\CONTRIBUTING.md, 544 , 2014-01-12
DeepLearnToolbox-master\create_readme.sh, 744 , 2014-01-12
DeepLearnToolbox-master\data, 0 , 2014-01-12
DeepLearnToolbox-master\data\mnist_uint8.mat, 14735220 , 2014-01-12
DeepLearnToolbox-master\DBN, 0 , 2019-08-01
DeepLearnToolbox-master\DBN\allcomb.m, 2618 , 2014-01-12
DeepLearnToolbox-master\DBN\dbnsetup.m, 557 , 2014-01-12
DeepLearnToolbox-master\DBN\dbntrain.m, 232 , 2014-01-12
DeepLearnToolbox-master\DBN\dbnunfoldtonn.m, 425 , 2014-01-12
DeepLearnToolbox-master\DBN\expand.m, 1958 , 2014-01-12
DeepLearnToolbox-master\DBN\flicker.m, 208 , 2014-01-12
DeepLearnToolbox-master\DBN\flipall.m, 80 , 2014-01-12
DeepLearnToolbox-master\DBN\fliplrf.m, 543 , 2014-01-12
DeepLearnToolbox-master\DBN\flipudf.m, 576 , 2014-01-12
DeepLearnToolbox-master\DBN\guzhangNumber.xls, 406528 , 2019-06-03
DeepLearnToolbox-master\DBN\im2patches.m, 313 , 2014-01-12
DeepLearnToolbox-master\DBN\isOctave.m, 108 , 2014-01-12
DeepLearnToolbox-master\DBN\makeLMfilters.m, 1895 , 2014-01-12
DeepLearnToolbox-master\DBN\mnist_uint8.mat, 14735220 , 2014-01-12
DeepLearnToolbox-master\DBN\myOctaveVersion.m, 169 , 2014-01-12
DeepLearnToolbox-master\DBN\nnapplygrads.m, 628 , 2014-01-12
DeepLearnToolbox-master\DBN\nnbp.m, 1638 , 2014-01-12
DeepLearnToolbox-master\DBN\nnchecknumgrad.m, 704 , 2014-01-12
DeepLearnToolbox-master\DBN\nneval.m, 772 , 2014-01-12
DeepLearnToolbox-master\DBN\nnff.m, 1849 , 2014-01-12
DeepLearnToolbox-master\DBN\nnpredict.m, 188 , 2014-01-12
DeepLearnToolbox-master\DBN\nnsetup.m, 1844 , 2014-01-12
DeepLearnToolbox-master\DBN\nntest.m, 180 , 2014-01-12
DeepLearnToolbox-master\DBN\nntrain.m, 2414 , 2014-01-12
DeepLearnToolbox-master\DBN\nnupdatefigures.m, 1858 , 2014-01-12
DeepLearnToolbox-master\DBN\normalize.m, 97 , 2014-01-12
DeepLearnToolbox-master\DBN\patches2im.m, 242 , 2014-01-12
DeepLearnToolbox-master\DBN\randcorr.m, 283 , 2014-01-12
DeepLearnToolbox-master\DBN\randp.m, 2083 , 2014-01-12
DeepLearnToolbox-master\DBN\rbmdown.m, 90 , 2014-01-12
DeepLearnToolbox-master\DBN\rbmtrain.m, 1401 , 2014-01-12
DeepLearnToolbox-master\DBN\rbmup.m, 89 , 2014-01-12
DeepLearnToolbox-master\DBN\rnd.m, 49 , 2014-01-12
DeepLearnToolbox-master\DBN\sigm.m, 48 , 2014-01-12
DeepLearnToolbox-master\DBN\sigmrnd.m, 126 , 2014-01-12
DeepLearnToolbox-master\DBN\softmax.m, 256 , 2014-01-12
DeepLearnToolbox-master\DBN\tanh_opt.m, 54 , 2014-01-12
DeepLearnToolbox-master\DBN\visualize.m, 1072 , 2014-01-12
DeepLearnToolbox-master\DBN\whiten.m, 183 , 2014-01-12
DeepLearnToolbox-master\DBN\zscore.m, 137 , 2014-01-12
DeepLearnToolbox-master\LICENSE, 1313 , 2014-01-12
DeepLearnToolbox-master\NN, 0 , 2014-01-12
DeepLearnToolbox-master\NN\nnapplygrads.m, 628 , 2014-01-12
DeepLearnToolbox-master\NN\nnbp.m, 1638 , 2014-01-12
DeepLearnToolbox-master\NN\nnchecknumgrad.m, 704 , 2014-01-12
DeepLearnToolbox-master\NN\nneval.m, 772 , 2014-01-12
DeepLearnToolbox-master\NN\nnff.m, 1849 , 2014-01-12
DeepLearnToolbox-master\NN\nnpredict.m, 188 , 2014-01-12
DeepLearnToolbox-master\NN\nnsetup.m, 1844 , 2014-01-12
DeepLearnToolbox-master\NN\nntest.m, 180 , 2014-01-12
DeepLearnToolbox-master\NN\nntrain.m, 2414 , 2014-01-12
DeepLearnToolbox-master\NN\nnupdatefigures.m, 1858 , 2014-01-12
DeepLearnToolbox-master\README.md, 8730 , 2014-01-12
DeepLearnToolbox-master\README_header.md, 2256 , 2014-01-12
DeepLearnToolbox-master\REFS.md, 950 , 2014-01-12
DeepLearnToolbox-master\SAE, 0 , 2014-01-12
DeepLearnToolbox-master\SAE\saesetup.m, 132 , 2014-01-12
DeepLearnToolbox-master\SAE\saetrain.m, 308 , 2014-01-12
DeepLearnToolbox-master\tests, 0 , 2014-01-12
DeepLearnToolbox-master\tests\runalltests.m, 165 , 2014-01-12
DeepLearnToolbox-master\tests\test_cnn_gradients_are_numerically_correct.m, 552 , 2014-01-12
DeepLearnToolbox-master\tests\test_example_CNN.m, 981 , 2014-01-12
DeepLearnToolbox-master\tests\test_example_DBN.m, 1644 , 2019-08-01
DeepLearnToolbox-master\tests\test_example_NN.m, 3247 , 2014-01-12
DeepLearnToolbox-master\tests\test_example_SAE.m, 934 , 2014-01-12
DeepLearnToolbox-master\tests\test_nn_gradients_are_numerically_correct.m, 749 , 2014-01-12
DeepLearnToolbox-master\util, 0 , 2014-01-12
DeepLearnToolbox-master\util\allcomb.m, 2618 , 2014-01-12
DeepLearnToolbox-master\util\expand.m, 1958 , 2014-01-12
DeepLearnToolbox-master\util\flicker.m, 208 , 2014-01-12
DeepLearnToolbox-master\util\flipall.m, 80 , 2014-01-12
DeepLearnToolbox-master\util\fliplrf.m, 543 , 2014-01-12

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

  • emd_imf_correlation
    这是应用emd分解之后,并与原信号进行相关分析的matlab程序(this is a program which contains emd and correlation analysis with the original signal)
    2011-11-09 14:36:33下载
    积分:1
  • feijimoni
    本程序对飞机在各种条件下的飞行状态进行模拟,并监测各参数的变化情况。(This program simulates the flight state of the aircraft under various conditions, and monitors the changes of the parameters.)
    2015-12-06 16:45:56下载
    积分:1
  • FCBF
    本代码是FCBF的源代码,用于处理连续型属性的特征选择,先将连续型属性值离散化,再筛选(This code is FCBF source code for handling continuous attributes feature selection, the first continuous discrete attribute values, re-screened)
    2016-07-05 17:17:49下载
    积分:1
  • Pcm_1
    PULSE CODE MODULATION(PCM)
    2014-09-05 13:02:26下载
    积分:1
  • Foundations-of-Fuzzy-Control---A-Practical-Approa
    Foundations of Fuzzy Control - A Practical Approach (2e) (C3-PPTX)
    2015-02-07 12:30:48下载
    积分:1
  • PAPER2
    The PAPR Problem in OFDM Transmission New Directions for a Long-Lasting Problem
    2015-02-24 13:29:40下载
    积分:1
  • microfluid
    利用有限元分析的方法,对微尺度内的物理进行了流动模拟,该方法可以分析多孔介质。(Finite element method, the physics of microscale flow simulation conducted, the method can analyze the porous media.)
    2010-09-27 09:10:58下载
    积分:1
  • yooxiangyuan2
    杆系结构的大量有限元MATLAB编程代码,,(Truss structures, a large number of finite element MATLAB programming code,)
    2013-05-20 21:10:37下载
    积分:1
  • AVO difference
    使用时移地震数据反演得到弹性参数相关变化量;(The correlation variation of elastic parameters is obtained by using time-lapse seismic data.)
    2017-12-05 15:40:09下载
    积分:1
  • pee
    Earthquake Engineering and Structural Dynamics(You can input any number of stores by giving the mass, stiffness and damping values. Input the gamma and beta values which are related to Newmark Integration Mtd. Press Newmarks Integration button to input the values. Input the any number of storey that you expected to see the deflection for particular Earthquake. Press “Storey No” button to get that number. If you like only, you will input the period and press “Period” button. Finally press calculate button to see final results. Also you can see the both graphs in log scales also.(Please right click on the graph as shown above). You may see what type of analysis method is used. (Average acceleration relation ship or Linear variation of acceleration).)
    2009-05-14 04:31:31下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载