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Title: CNN 11 tezhengtiqu Download
  • Category:
  • Other systems
  • Tags:
  • File Size:
  • 38.55mb
  • Update:
  • 2018-05-01
  • Downloads:
  • 0 Times
  • Uploaded by:
  • 乳山人
 Description: Convolution neural network is used for fault diagnosis and achieves good recognition results.
 Downloaders recently: [More information of uploader 乳山人]
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File list (Check if you may need any files): 
FilenameSizeDate
CNN 11 tezhengtiqu\allcomb.m 2618  2015-12-01

CNN 11 tezhengtiqu\bishedata_jiang.mat 24907516  2018-04-12

CNN 11 tezhengtiqu\cnnapplygrads.m 904  2018-04-11

CNN 11 tezhengtiqu\cnnbp.m 4317  2018-04-11

CNN 11 tezhengtiqu\cnnff.m 3421  2018-04-16

CNN 11 tezhengtiqu\cnnnumgradcheck.m 3430  2015-12-01

CNN 11 tezhengtiqu\cnnsetup.m 3087  2018-04-16

CNN 11 tezhengtiqu\cnntest.m 257  2018-04-18

CNN 11 tezhengtiqu\cnntrain.m 2599  2018-04-29

CNN 11 tezhengtiqu\data_curve.m 778  2018-04-25

CNN 11 tezhengtiqu\divide_TrainTest.m 609  2018-04-19

CNN 11 tezhengtiqu\envelope_spectrum.m 818  2018-04-16

CNN 11 tezhengtiqu\expand.m 1958  2015-12-01

CNN 11 tezhengtiqu\feature_envelope_extraction.m 888  2018-04-16

CNN 11 tezhengtiqu\feature_extraction.m 897  2018-04-19

CNN 11 tezhengtiqu\feature_frequency_extraction.m 904  2018-04-16

CNN 11 tezhengtiqu\feature_main.m 1680  2018-04-17

CNN 11 tezhengtiqu\feature_process_CNN.m 2564  2018-04-27

CNN 11 tezhengtiqu\feature_time_extraction.m 2490  2018-04-15

CNN 11 tezhengtiqu\flicker.m 208  2015-12-01

CNN 11 tezhengtiqu\flipall.m 93  2018-04-11

CNN 11 tezhengtiqu\fliplrf.m 543  2015-12-01

CNN 11 tezhengtiqu\flipudf.m 576  2015-12-01

CNN 11 tezhengtiqu\frequency_spectrum.m 421  2018-04-16

CNN 11 tezhengtiqu\gear_fault_featuredata.mat 448941  2018-04-30

CNN 11 tezhengtiqu\gear_fault_featuredata_jiang.mat 298975  2018-04-30

CNN 11 tezhengtiqu\im2patches.m 313  2015-12-01

CNN 11 tezhengtiqu\isOctave.m 108  2015-12-01

CNN 11 tezhengtiqu\makeLMfilters.m 1895  2015-12-01

CNN 11 tezhengtiqu\mnist_uint8.mat 14735220  2015-12-01

CNN 11 tezhengtiqu\myOctaveVersion.m 169  2015-12-01

CNN 11 tezhengtiqu\normalize.m 97  2015-12-01

CNN 11 tezhengtiqu\patches2im.m 242  2015-12-01

CNN 11 tezhengtiqu\randcorr.m 283  2015-12-01

CNN 11 tezhengtiqu\randp.m 2083  2015-12-01

CNN 11 tezhengtiqu\rnd.m 49  2015-12-01

CNN 11 tezhengtiqu\sigm.m 48  2015-12-01

CNN 11 tezhengtiqu\sigmrnd.m 126  2015-12-01

CNN 11 tezhengtiqu\softmax.m 256  2015-12-01

CNN 11 tezhengtiqu\tanh_opt.m 54  2015-12-01

CNN 11 tezhengtiqu\testing_accuracy.tif 51533  2018-04-30

CNN 11 tezhengtiqu\testing_error.tif 49093  2018-04-30

CNN 11 tezhengtiqu\training_accuracy.tif 51347  2018-04-30

CNN 11 tezhengtiqu\training_error.tif 48795  2018-04-30

CNN 11 tezhengtiqu\visualize.m 1072  2015-12-01

CNN 11 tezhengtiqu\whiten.m 183  2015-12-01

CNN 11 tezhengtiqu\zscore.m 137  2015-12-01

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