登录
首页 » matlab » DeepLearnToolbox-master

DeepLearnToolbox-master

于 2020-06-19 发布
0 157
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

  • danyonghu
    单用户超宽带通信系统仿真,基于线性调频信号(single-user UWB communication system simulation, based on the linear FM signal)
    2007-01-10 13:25:52下载
    积分:1
  • fisheye11111
    鱼眼畸变校正的论文可以下载国外比较经典的(Fish-eye distortion correction of the paper can be downloaded outside of the more classic)
    2011-08-30 11:37:29下载
    积分:1
  • ofdm_4qam
    子载波数128位数/ 符号 2符号数/ 载波 1000训练符号数 0循环前缀长度8 调制方式 4-QAM多径信道数3 IFFT Size128 信道最大时延 2(ofdm program 4QAM modulation. Subcarriers median number of 128 /2 Symbol Symbol/carrier cyclic prefix length of the number of training symbols of 1000 0 8 modulation mode 4-QAM multi-path channel number 3 the IFFT Size 128 channel maximum delay)
    2013-05-13 18:33:43下载
    积分:1
  • mocvd
    这是计算光子晶体程序,对研究光子晶体的同行很有用(This is the calculation procedures for photonic crystals, photonic crystals to study the usefulness of the peer)
    2009-03-28 09:44:59下载
    积分:1
  • MATLAB6.5
    说明:  matlab基础教程,适合初学者的基础学习matlab。以及有一定基础者的进阶(matlab basic tutorial for beginners to learn the basis of matlab. And those who have some basic advanced)
    2011-03-19 11:49:48下载
    积分:1
  • CODEProgram27_FDTD_2D_with_Mur_ABC_boundary
    2D FDTD of a region with Mur s absorbing boundary
    2012-06-02 15:22:09下载
    积分:1
  • ComElectrom
    FEM with 2D scattering from perfect cylinder
    2009-05-02 12:52:53下载
    积分:1
  • filterbank
    The idea of a filterbank on a non-linear(mel) frequency scale(filter bank for mel)
    2010-11-09 21:29:51下载
    积分:1
  • hecigongzhen
    核磁共振方法是一项尖端技术,在物理学和医学等领域有着较普遍的应用。 其无损性和高分辨率的特点是这项技术最大的优势。而利用核磁共振方法来找水 是其在地学中应用的一个新领域,为地球物理方法提供了新的思路。(NMR is a cutting-edge technology, medicine and other fields in physics and has more general application. The high-resolution non-destructive and are characterized by the biggest advantage of this technology. The use of NMR to come to learn that water is applied in a new area for geophysical methods to provide a new way of thinking.)
    2011-08-08 15:53:05下载
    积分:1
  • matlab-gui
    Matlab program for railway abnormal detection and imaging,including GUI, open dlg, processing dlg and source code.
    2013-08-22 17:04:58下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载