登录
首页 » matlab » 多任务深度学习改进版

多任务深度学习改进版

于 2018-11-17 发布 文件大小:14428KB
0 232
下载积分: 1 下载次数: 7

代码说明:

  这个程序实现了多任务的深度学习,可以提高训练的收敛速度(Multi-task deep learning)

文件列表:

多任务深度学习改进版\Calculate_Bin_Num.m, 150 , 2018-07-27
多任务深度学习改进版\Check_error.m, 1810 , 2018-07-27
多任务深度学习改进版\Construct_start_end_tab.m, 593 , 2018-07-27
多任务深度学习改进版\dbnunfoldtonn1.m, 534 , 2018-07-27
多任务深度学习改进版\dbnunfoldtonn2.m, 447 , 2018-07-27
多任务深度学习改进版\dbnunfoldtonn3.m, 482 , 2018-08-04
多任务深度学习改进版\DBN_SFC.m, 2972 , 2018-09-12
多任务深度学习改进版\Decrease_zeros.m, 639 , 2018-07-27
多任务深度学习改进版\denose.m, 862 , 2018-07-27
多任务深度学习改进版\Equal.m, 1668 , 2018-07-27
多任务深度学习改进版\Load_Data_Set.m, 689 , 2018-09-10
多任务深度学习改进版\mlt_nnff.m, 3320 , 2018-09-03
多任务深度学习改进版\mlt_nntrain.m, 4073 , 2018-08-04
多任务深度学习改进版\mtl_dbntrain.m, 738 , 2018-08-04
多任务深度学习改进版\mtl_nnbp.m, 5478 , 2018-08-04
多任务深度学习改进版\mtl_nneval.m, 1447 , 2018-08-04
多任务深度学习改进版\mtl_nnpredict.m, 788 , 2018-08-04
多任务深度学习改进版\mtl_nntest.m, 536 , 2018-08-04
多任务深度学习改进版\mulitask_DBN.m, 4658 , 2018-09-06
多任务深度学习改进版\nnsetup1.m, 2622 , 2018-07-27
多任务深度学习改进版\nnsetup2.m, 1871 , 2018-08-03
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\.travis.yml, 249 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\caeapplygrads.m, 1219 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\caebbp.m, 917 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\caebp.m, 1011 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\caedown.m, 259 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\caeexamples.m, 754 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\caenumgradcheck.m, 3618 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\caesdlm.m, 845 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\caetrain.m, 1148 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\caeup.m, 489 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\max3d.m, 173 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\scaesetup.m, 1937 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CAE\scaetrain.m, 270 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CNN\cnnapplygrads.m, 575 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CNN\cnnbp.m, 2141 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CNN\cnnff.m, 1774 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CNN\cnnnumgradcheck.m, 3430 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CNN\cnnsetup.m, 2020 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CNN\cnntest.m, 193 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CNN\cnntrain.m, 845 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\CONTRIBUTING.md, 544 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\create_readme.sh, 744 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\data\mnist_uint8.mat, 14735220 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\DBN\dbnsetup.m, 557 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\DBN\dbntrain.m, 232 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\DBN\dbnunfoldtonn.m, 425 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\DBN\rbmdown.m, 90 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\DBN\rbmtrain.m, 1401 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\DBN\rbmup.m, 89 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\LICENSE, 1313 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nnapplygrads.m, 628 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nnbp.m, 1638 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nnchecknumgrad.m, 704 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nneval.m, 811 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nnff.m, 1904 , 2017-12-20
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nnpredict.m, 357 , 2017-12-27
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nnsetup.m, 1840 , 2017-12-28
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nntest.m, 202 , 2017-07-31
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nntrain.m, 2414 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\NN\nnupdatefigures.m, 1858 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\README.md, 8861 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\README_header.md, 2244 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\REFS.md, 950 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\SAE\saesetup.m, 132 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\SAE\saetrain.m, 308 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\tests\runalltests.m, 165 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\tests\test_cnn_gradients_are_numerically_correct.m, 552 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\tests\test_example_CNN.m, 981 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\tests\test_example_DBN.m, 1031 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\tests\test_example_NN.m, 3247 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\tests\test_example_SAE.m, 934 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\tests\test_nn_gradients_are_numerically_correct.m, 749 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\allcomb.m, 2618 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\expand.m, 1958 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\flicker.m, 208 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\flipall.m, 80 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\fliplrf.m, 543 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\flipudf.m, 576 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\im2patches.m, 313 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\isOctave.m, 108 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\makeLMfilters.m, 1895 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\myOctaveVersion.m, 169 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\normalize.m, 97 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\patches2im.m, 242 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\randcorr.m, 283 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\randp.m, 2083 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\rnd.m, 49 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\sigm.m, 48 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\sigmrnd.m, 126 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\softmax.m, 256 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\tanh_opt.m, 54 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\visualize.m, 1072 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\whiten.m, 183 , 2015-12-01
多任务深度学习改进版\rasmusbergpalm-DeepLearnToolbox-5df2801\rasmusbergpalm-DeepLearnToolbox-5df2801\util\zscore.m, 137 , 2015-12-01
多任务深度学习改进版\spilt_train_x.m, 377 , 2018-08-04
多任务深度学习改进版\tri_nnapplygrads.m, 2231 , 2018-07-27
多任务深度学习改进版\测试程序\ceshi_nnff.asv, 2894 , 2018-09-13
多任务深度学习改进版\测试程序\ceshi_nnff.m, 3404 , 2018-09-13
多任务深度学习改进版\测试程序\fenzushuju_andian.asv, 577 , 2018-09-12

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

  • 移动硬盘盒的电路,包括电路原理图和电路板。
    移动硬盘盒的电路图,包括原理图和PCB。-Mobile hard disk box of circuitry, including schematic and PCB.
    2022-01-26 05:11:19下载
    积分:1
  • 这时候图形学里面用的橡皮筋直线,可以自己用键盘设计起点,用左右方向键控制直线走向...
    这时候图形学里面用的橡皮筋直线,可以自己用键盘设计起点,用左右方向键控制直线走向-this time graphics inside the rubber-band linear, his keyboard design starting point, use the direction keys around to control line
    2022-05-15 11:03:03下载
    积分:1
  • 示波器
    给大家上传一个用Labview做的示波器供大家参考!里面有源程序,大家可以套用。(To upload a Labview oscilloscope for your reference! There are active programs, you can apply them.)
    2019-03-28 14:54:51下载
    积分:1
  • EDFQswitch
    光纤激光器被动调Q速率方程,修改参数可实现三能级四能级激光器模拟(Passive Q-rate equation of fiber laser)
    2019-04-14 10:02:26下载
    积分:1
  • 使用Access数据库演示的任务分配管理程序 一个使用ADO.NET基于Microsoft Access数据库演示的任务分配管理的程序,用于.NET...
    使用Access数据库演示的任务分配管理程序 一个使用ADO.NET基于Microsoft Access数据库演示的任务分配管理的程序,用于.NET Framework-based和COM程序。程序功能演示添加、删除、修改任务,用户权限指派,一个比较详细的数据库演示示例程序。以前就预备了,由于近期FTP无法登录再加上VS.NET2005开发环境到期(呵呵,以前安装的是使用180天版,今天刚在枕善居论坛下载了破解补丁,补丁地址在本居的论坛里,有需要的朋友去下载吧)。 说明:本程序基于VS.NET2005-Access database demonstration using the distribution of mission management procedures using ADO.NET on Microsoft Access database management presentation of the task allocation procedure, for. NET Framework-based and COM procedures. Demonstration program features add, delete, modify tasks, assign user rights, a more detailed presentation of the database sample programs. Previously prepared, FTP can not log in due to the recent VS.NET2005 development environment coupled with the expiration of (Oh, the previously installed version is the use of 180 days, today just good pillow Habitat Forum downloaded crack patch, patch the address in the home forums, there is a need friends to download it). Description: This procedure based on VS
    2022-10-26 06:30:02下载
    积分:1
  • 图形模式下读写屏幕的C程序
    图形模式下读写屏幕的C程序-graphics mode screen reader C Program
    2022-12-30 01:00:04下载
    积分:1
  • huanyingdenglu
    用LABVIEW做的欢迎界面,可以设置分类型号登陆,对坐测试的朋友有一定的帮助,尤其是多型号测试。(Welcome to do with the LABVIEW interface, you can set the classification models landing, sitting down to a test of a friend has some help, especially the multi-model test.)
    2010-08-28 08:31:06下载
    积分:1
  • lstm
    循环神经网络LSTM可以预测时间序列数据,根据历史时刻的信息预测未来时刻的信息(the recurrent neural network is very useful to predict data in the future)
    2020-08-30 16:08:10下载
    积分:1
  • bayes-location
    关于室内定位算法的比较,主要是利用贝叶斯的方法进行(Comparison of indoor location algorithms)
    2020-07-04 17:00:01下载
    积分:1
  • Lin_Deep_Learning_of_2015_CVPR_paper
    这是一篇关于图像检索的文章,主要内容如下:在第2部分对哈希算法的相关工作和基于深度学习的图像检索进行了回顾,在第3部分详述了所提出的一个新颖算法,最后,在第4部分和第5部分分别给出了实验结果和结论。(This paper is organized as follows: the related work of hashing algorithms and image retrieval with deep learning are briefly reviewed in Section 2. the details of a new method is elaborated on in Section 3. Finally, experimental results are provided in Section 4, followed by conclusions in Section 5.)
    2020-06-22 00:20:02下载
    积分:1
  • 696516资源总数
  • 106405会员总数
  • 10今日下载