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DeepLearnToolbox-master

于 2020-12-16 发布
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下载积分: 1 下载次数: 3

代码说明:

说明:  深度学习的工具箱,里面有卷积神经网络等的一些代码(Deep learning toolbox, which contains some codes such as convolutional neural network.)

文件列表:

DeepLearnToolbox-master\.travis.yml, 249 , 2015-12-01
DeepLearnToolbox-master\CAE\caeapplygrads.m, 1219 , 2015-12-01
DeepLearnToolbox-master\CAE\caebbp.m, 917 , 2015-12-01
DeepLearnToolbox-master\CAE\caebp.m, 1011 , 2015-12-01
DeepLearnToolbox-master\CAE\caedown.m, 259 , 2015-12-01
DeepLearnToolbox-master\CAE\caeexamples.m, 754 , 2015-12-01
DeepLearnToolbox-master\CAE\caenumgradcheck.m, 3618 , 2015-12-01
DeepLearnToolbox-master\CAE\caesdlm.m, 845 , 2015-12-01
DeepLearnToolbox-master\CAE\caetrain.m, 1148 , 2015-12-01
DeepLearnToolbox-master\CAE\caeup.m, 489 , 2015-12-01
DeepLearnToolbox-master\CAE\max3d.m, 173 , 2015-12-01
DeepLearnToolbox-master\CAE\scaesetup.m, 1937 , 2015-12-01
DeepLearnToolbox-master\CAE\scaetrain.m, 270 , 2015-12-01
DeepLearnToolbox-master\CNN\cnnapplygrads.m, 575 , 2015-12-01
DeepLearnToolbox-master\CNN\cnnbp.m, 2141 , 2015-12-01
DeepLearnToolbox-master\CNN\cnnff.m, 1774 , 2015-12-01
DeepLearnToolbox-master\CNN\cnnnumgradcheck.m, 3430 , 2015-12-01
DeepLearnToolbox-master\CNN\cnnsetup.m, 2020 , 2015-12-01
DeepLearnToolbox-master\CNN\cnntest.m, 193 , 2015-12-01
DeepLearnToolbox-master\CNN\cnntrain.m, 845 , 2015-12-01
DeepLearnToolbox-master\CONTRIBUTING.md, 544 , 2015-12-01
DeepLearnToolbox-master\create_readme.sh, 744 , 2015-12-01
DeepLearnToolbox-master\data\mnist_uint8.mat, 14735220 , 2015-12-01
DeepLearnToolbox-master\DBN\dbnsetup.m, 557 , 2015-12-01
DeepLearnToolbox-master\DBN\dbntrain.m, 232 , 2015-12-01
DeepLearnToolbox-master\DBN\dbnunfoldtonn.m, 425 , 2015-12-01
DeepLearnToolbox-master\DBN\rbmdown.m, 90 , 2015-12-01
DeepLearnToolbox-master\DBN\rbmtrain.m, 1401 , 2015-12-01
DeepLearnToolbox-master\DBN\rbmup.m, 89 , 2015-12-01
DeepLearnToolbox-master\LICENSE, 1313 , 2015-12-01
DeepLearnToolbox-master\NN\nnapplygrads.m, 628 , 2015-12-01
DeepLearnToolbox-master\NN\nnbp.m, 1638 , 2015-12-01
DeepLearnToolbox-master\NN\nnchecknumgrad.m, 704 , 2015-12-01
DeepLearnToolbox-master\NN\nneval.m, 811 , 2015-12-01
DeepLearnToolbox-master\NN\nnff.m, 1849 , 2015-12-01
DeepLearnToolbox-master\NN\nnpredict.m, 192 , 2015-12-01
DeepLearnToolbox-master\NN\nnsetup.m, 1844 , 2015-12-01
DeepLearnToolbox-master\NN\nntest.m, 184 , 2015-12-01
DeepLearnToolbox-master\NN\nntrain.m, 2414 , 2015-12-01
DeepLearnToolbox-master\NN\nnupdatefigures.m, 1858 , 2015-12-01
DeepLearnToolbox-master\README.md, 8861 , 2015-12-01
DeepLearnToolbox-master\README_header.md, 2244 , 2015-12-01
DeepLearnToolbox-master\REFS.md, 950 , 2015-12-01
DeepLearnToolbox-master\SAE\saesetup.m, 132 , 2015-12-01
DeepLearnToolbox-master\SAE\saetrain.m, 308 , 2015-12-01
DeepLearnToolbox-master\tests\runalltests.m, 165 , 2015-12-01
DeepLearnToolbox-master\tests\test_cnn_gradients_are_numerically_correct.m, 552 , 2015-12-01
DeepLearnToolbox-master\tests\test_example_CNN.m, 981 , 2015-12-01
DeepLearnToolbox-master\tests\test_example_DBN.m, 1031 , 2015-12-01
DeepLearnToolbox-master\tests\test_example_NN.m, 3247 , 2015-12-01
DeepLearnToolbox-master\tests\test_example_SAE.m, 934 , 2015-12-01
DeepLearnToolbox-master\tests\test_nn_gradients_are_numerically_correct.m, 749 , 2015-12-01
DeepLearnToolbox-master\util\allcomb.m, 2618 , 2015-12-01
DeepLearnToolbox-master\util\expand.m, 1958 , 2015-12-01
DeepLearnToolbox-master\util\flicker.m, 208 , 2015-12-01
DeepLearnToolbox-master\util\flipall.m, 80 , 2015-12-01
DeepLearnToolbox-master\util\fliplrf.m, 543 , 2015-12-01
DeepLearnToolbox-master\util\flipudf.m, 576 , 2015-12-01
DeepLearnToolbox-master\util\im2patches.m, 313 , 2015-12-01
DeepLearnToolbox-master\util\isOctave.m, 108 , 2015-12-01
DeepLearnToolbox-master\util\makeLMfilters.m, 1895 , 2015-12-01
DeepLearnToolbox-master\util\myOctaveVersion.m, 169 , 2015-12-01
DeepLearnToolbox-master\util\normalize.m, 97 , 2015-12-01
DeepLearnToolbox-master\util\patches2im.m, 242 , 2015-12-01
DeepLearnToolbox-master\util\randcorr.m, 283 , 2015-12-01
DeepLearnToolbox-master\util\randp.m, 2083 , 2015-12-01
DeepLearnToolbox-master\util\rnd.m, 49 , 2015-12-01
DeepLearnToolbox-master\util\sigm.m, 48 , 2015-12-01
DeepLearnToolbox-master\util\sigmrnd.m, 126 , 2015-12-01
DeepLearnToolbox-master\util\softmax.m, 256 , 2015-12-01
DeepLearnToolbox-master\util\tanh_opt.m, 54 , 2015-12-01
DeepLearnToolbox-master\util\visualize.m, 1072 , 2015-12-01
DeepLearnToolbox-master\util\whiten.m, 183 , 2015-12-01
DeepLearnToolbox-master\util\zscore.m, 137 , 2015-12-01
DeepLearnToolbox-master\CAE, 0 , 2015-12-01
DeepLearnToolbox-master\CNN, 0 , 2015-12-01
DeepLearnToolbox-master\data, 0 , 2015-12-01
DeepLearnToolbox-master\DBN, 0 , 2015-12-01
DeepLearnToolbox-master\NN, 0 , 2015-12-01
DeepLearnToolbox-master\SAE, 0 , 2015-12-01
DeepLearnToolbox-master\tests, 0 , 2015-12-01
DeepLearnToolbox-master\util, 0 , 2015-12-01
DeepLearnToolbox-master, 0 , 2015-12-01

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发表评论

0 个回复

  • aa
    说明:  在同一张图上仿真多幅度电平M电平PAM在M=2,4,8,16时的符号差错概率。(In the same graph simulation multi-level rate of M-level PAM at M = 2,4,8,16 when the symbol error probability.)
    2010-06-03 14:19:21下载
    积分:1
  • SMO_sevo
    这是一个基于关于伺服系统的滑模控制的仿真程序,伺服系统为基于S的数学模型,对于研究滑模控制会有帮助(sliding mode control of the sevo system)
    2010-06-23 22:03:27下载
    积分:1
  • dongtaiwenben
    在背景为纯色的情况下,能够用色调来代替Alpha,而色调虽然是特效,但是他实际上只是颜色的复合,结果让文本显示单一颜色,调用(In the background for the pure color, can coloring attune instead of Alpha, and tonal though is the special effects, but he is actually the color composite, the result let text display a single color, calls)
    2012-02-10 23:12:26下载
    积分:1
  • tuxiangshiyan
    图像中值滤波的改进算法 频域中的图像去噪算法 matlab实验(matlab experiments )
    2009-05-04 23:20:19下载
    积分:1
  • SOAmodel
    该程序系统的模拟了半导体光放大器的物理模型,对研究半导体光放大器非常有用!!(The program system to simulate the physical model of semiconductor optical amplifiers, semiconductor optical amplifiers for research is very useful! !)
    2021-04-08 20:29:00下载
    积分:1
  • targetdistance
    对不同距离的雷达回波进行脉冲压缩处理,观察脉冲压缩后的回波信号,分析个参数对其的影响(Distances for different pulse compression radar echo , the echo pulse compression observed signal parameters and the effects of )
    2013-11-12 19:40:05下载
    积分:1
  • M-PSK
    4psk&8psk的matlab实现,采用蒙特卡罗仿真法,计算误码率误比特率,绘制相应曲线(the realization of 4psk&8psk by Matlab tool,it use Monte Carlo way to calculate the BER and draw the graph.)
    2005-06-13 00:52:32下载
    积分:1
  • Assignment6
    used to calculate matrices opeartion
    2010-12-29 00:27:24下载
    积分:1
  • 2008101523144260
    说明:  一、用GA直接训练BP网络的权重算法 主程序:gafault.m 它包括以下子程序: 1. BP网络初始化:nninit.m――给出P,T,R,S1,S2; 2. 适应值计算函数:gabpEval.m; 3.将遗传算法的编码解码为BP网络所对应的权值、阈值函数:gadecod.m; 二、用GA先求BP网络的权重,再用纯BP直接训练BP的混合GA-BP算法 主程序:gabpfault.m 它包括以下子程序: 1. 网络初始化:nninit.m――给出P,T,R,S1,S2; 2. 适应值计算函数:gabpEval.m; 3.将遗传算法的编码解码为BP网络所对应的权值、阈值函数:gadecod.m; 三、纯BP   主程序:(1)bpfault.m 在MATLAB5.2上       (2)bpfault.m 在MATLAB6.5上 为后来所加 (err)
    2008-10-16 08:20:54下载
    积分:1
  • quanxizhenduan
    全系诊断是应用广泛的信号处理技术,能够给出大量的振动信号中的信息(The entire department diagnosis is widely used in signal processing technology to give a large number of vibration signals of the information)
    2010-03-05 16:10:11下载
    积分:1
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