DeepNeuralNetwork20131115
所属分类:人工智能/神经网络/深度学习
开发工具:matlab
文件大小:4677KB
下载次数:88
上传日期:2013-11-18 11:18:49
上 传 者:
nomad21
说明: DBNS的深度学习工具
(Run testDNN to try!
Each function includes description. Please check it!
It provides deep learning tools of deep belief networks (DBNs) of stacked restricted Boltzmann machines (RBMs). It includes the Bernoulli-Bernoulli RBM, the Gaussian-Bernoulli RBM, the contrastive divergence learning for unsupervised pre-training, the sparse constraint, the back projection for supervised training, and the dropout technique.
The sample codes with the MNIST dataset are included in the mnist folder. Please, see readme.txt in the mnist folder.
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文件列表:
DeepNeuralNetwork (0, 2013-11-16)
DeepNeuralNetwork\randRBM.m (1358, 2013-11-06)
DeepNeuralNetwork\testDNN.m (481, 2013-11-08)
DeepNeuralNetwork\mnist (0, 2013-11-16)
DeepNeuralNetwork\mnist\mnistbbdbn.mat (4770186, 2013-11-15)
DeepNeuralNetwork\mnist\evaMNIST.m (879, 2013-11-15)
DeepNeuralNetwork\mnist\trainMNIST.m (1502, 2013-11-15)
DeepNeuralNetwork\mnist\mnistread.m (1884, 2013-11-14)
DeepNeuralNetwork\mnist\testMNIST.m (22, 2013-11-16)
DeepNeuralNetwork\pretrainDBN.m (2876, 2013-11-06)
DeepNeuralNetwork\v2hall.m (1242, 2013-11-06)
DeepNeuralNetwork\CalcRmse.m (1138, 2013-11-06)
DeepNeuralNetwork\trainDBN.m (7494, 2013-11-08)
DeepNeuralNetwork\linearMapping.m (1128, 2013-11-06)
DeepNeuralNetwork\CalcErrorRate.m (998, 2013-11-15)
DeepNeuralNetwork\GetOnInd.m (1357, 2013-11-06)
DeepNeuralNetwork\randDBN.m (1484, 2013-11-06)
DeepNeuralNetwork\h2v.m (1516, 2013-11-06)
DeepNeuralNetwork\sigmoid.m (618, 2013-11-06)
DeepNeuralNetwork\v2h.m (1527, 2013-11-06)
DeepNeuralNetwork\SetLinearMapping.m (1690, 2013-11-06)
DeepNeuralNetwork\pretrainRBM.m (6296, 2013-11-06)
DeepNeuralNetwork\GetDroppedDBN.m (1935, 2013-11-06)
license.txt (1315, 2013-11-16)
mnistdbdn.mat: trained dnn
mnistread.m: function to read the MNIST data
trainMNIST.m: sample code of training with the MNIST data
evaMNIST.m: sample code of evaluation of mnistdbdn.mat
testMNIST.m: it calls trainMNIST and evaMNIST
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