DNN
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：20703KB
下载次数：5
上传日期：2021-03-02 17:18:18
上 传 者：
AIKO123
说明： 深度神经网络DNN，可用于多目标的最优规划问题。
(The deep neural network DNN can be used for multi-objective optimal planning problems.)
文件列表:
DeepNeuralNetwork20160805 (0, 2020-07-03)
DeepNeuralNetwork20160805\DeepNeuralNetwork (0, 2020-07-03)
DeepNeuralNetwork20160805\DeepNeuralNetwork\CalcErrorRate.m (1030, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\CalcRmse.m (1138, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\DeepNeuralNetwork20160805.mltbx (4813902, 2018-04-20)
DeepNeuralNetwork20160805\DeepNeuralNetwork\GetDroppedDBN.m (1935, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\GetOnInd.m (1357, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\ObjectFunc.m (673, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\SetLinearMapping.m (1690, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\h2v.m (1794, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\linearMapping.m (1128, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist (0, 2020-07-03)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist\evaMNIST.m (1124, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist\mnistbbdbn.mat (4770186, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist\mnistread.m (1884, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist\t10k-images-idx3-ubyte (1648877, 2018-04-23)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist\t10k-labels-idx1-ubyte (4542, 2018-04-23)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist\testMNIST.m (22, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist\train-images-idx3-ubyte (9912422, 2018-04-23)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist\train-labels-idx1-ubyte (28881, 2018-04-23)
DeepNeuralNetwork20160805\DeepNeuralNetwork\mnist\trainMNIST.m (1502, 2018-04-23)
DeepNeuralNetwork20160805\DeepNeuralNetwork\pretrainDBN.m (2876, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\pretrainRBM.m (6644, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\randDBN.m (1611, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\randRBM.m (1355, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\sigmoid.m (618, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\testDNN.m (542, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\trainDBN.m (12217, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\v2h.m (1795, 2016-08-04)
DeepNeuralNetwork20160805\DeepNeuralNetwork\v2hall.m (1262, 2016-08-04)
DeepNeuralNetwork20160805\license.txt (1315, 2016-08-04)
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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