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ruan zhu

于 2020-07-09 发布
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下载积分: 1 下载次数: 1
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代码说明：

说明：  一个用DBN做时间序列预测的实例，内包括了数据(An example of using DBN to predict time series includes data)

文件列表：

ruan zhu\choose.fig, 6677 , 2020-07-03
ruan zhu\choose.m, 3556 , 2020-01-11
ruan zhu\contact.fig, 7981 , 2020-07-03
ruan zhu\contact.m, 3495 , 2020-07-03
ruan zhu\cross.m, 306 , 2018-01-12
ruan zhu\DeepLearnToolbox\2019负荷.xlsx, 243570 , 2020-03-27
ruan zhu\DeepLearnToolbox\EMDDBN\AEMO_importdata_one.m, 1068 , 2020-07-03
ruan zhu\DeepLearnToolbox\EMDDBN\AEMO_importdata_two.m, 1068 , 2020-07-03
ruan zhu\DeepLearnToolbox\EMDDBN\Datasets\AEMO_NSW.mat, 68825 , 2014-09-16
ruan zhu\DeepLearnToolbox\EMDDBN\Datasets\AEMO_QLD.mat, 66211 , 2015-01-04
ruan zhu\DeepLearnToolbox\EMDDBN\Datasets\AEMO_SA.mat, 58170 , 2014-09-16
ruan zhu\DeepLearnToolbox\EMDDBN\Datasets\AEMO_TAS.mat, 55411 , 2014-09-16
ruan zhu\DeepLearnToolbox\EMDDBN\Datasets\AEMO_VIC.mat, 67017 , 2015-07-02
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\.travis.yml, 249 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\caeapplygrads.m, 1219 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\caebbp.m, 917 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\caebp.m, 1011 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\caedown.m, 259 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\caeexamples.m, 754 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\caenumgradcheck.m, 3618 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\caesdlm.m, 845 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\caetrain.m, 1148 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\caeup.m, 489 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\max3d.m, 173 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\scaesetup.m, 1937 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CAE\scaetrain.m, 270 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CNN\cnnapplygrads.m, 575 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CNN\cnnbp.m, 2141 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CNN\cnnff.m, 1774 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CNN\cnnnumgradcheck.m, 3430 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CNN\cnnsetup.m, 2020 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CNN\cnntest.m, 193 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CNN\cnntrain.m, 845 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\CONTRIBUTING.md, 544 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\create_readme.sh, 744 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\data\mnist_uint8.mat, 14735220 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\DBN\dbnsetup.m, 557 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\DBN\dbntrain.m, 232 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\DBN\dbnunfoldtonn.m, 425 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\DBN\rbmdown.m, 90 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\DBN\rbmtrain.m, 1401 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\DBN\rbmup.m, 89 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\LICENSE, 1313 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nnapplygrads.m, 628 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nnbp.m, 1638 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nnchecknumgrad.m, 704 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nneval.m, 811 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nnff.m, 1848 , 2019-04-30
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nnpredict.m, 192 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nnsetup.m, 1844 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nntest.m, 184 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nntrain.m, 2415 , 2019-04-22
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\NN\nnupdatefigures.m, 1858 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\README.md, 8730 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\README_header.md, 2256 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\REFS.md, 950 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\SAE\saesetup.m, 132 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\SAE\saetrain.m, 308 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\tests\runalltests.m, 165 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\tests\test_cnn_gradients_are_numerically_correct.m, 552 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\tests\test_example_CNN.m, 981 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\tests\test_example_DBN.m, 1031 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\tests\test_example_NN.m, 3247 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\tests\test_example_SAE.m, 934 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\tests\test_nn_gradients_are_numerically_correct.m, 749 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\allcomb.m, 2618 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\expand.m, 1958 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\flicker.m, 208 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\flipall.m, 80 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\fliplrf.m, 543 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\flipudf.m, 576 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\im2patches.m, 313 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\isOctave.m, 108 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\makeLMfilters.m, 1895 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\myOctaveVersion.m, 169 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\normalize.m, 97 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\patches2im.m, 242 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\randcorr.m, 283 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\randp.m, 2083 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\rnd.m, 49 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\sigm.m, 48 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\sigmrnd.m, 126 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\softmax.m, 256 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\tanh_opt.m, 54 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\visualize.m, 1072 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\whiten.m, 183 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\deeplearning\util\zscore.m, 137 , 2014-06-26
ruan zhu\DeepLearnToolbox\EMDDBN\EMD_DBN_one.m, 3964 , 2020-07-03
ruan zhu\DeepLearnToolbox\EMDDBN\EMD_DBN_two.m, 3935 , 2020-07-03
ruan zhu\DeepLearnToolbox\EMDDBN\errormeasure.m, 631 , 2017-03-30
ruan zhu\DeepLearnToolbox\EMDDBN\errperf.m, 5289 , 2019-04-22
ruan zhu\DeepLearnToolbox\EMDDBN\nnpredicty.m, 140 , 2014-07-06
ruan zhu\DeepLearnToolbox\EMDDBN\package_emd\bugfix.sh, 216 , 2015-03-11
ruan zhu\DeepLearnToolbox\EMDDBN\package_emd\EMDs\cemdc.m, 2354 , 2015-03-11
ruan zhu\DeepLearnToolbox\EMDDBN\package_emd\EMDs\cemdc2.m, 2362 , 2015-03-11
ruan zhu\DeepLearnToolbox\EMDDBN\package_emd\EMDs\cemdc2_fix.m, 2312 , 2015-03-11
ruan zhu\DeepLearnToolbox\EMDDBN\package_emd\EMDs\cemdc_fix.m, 2305 , 2015-03-11
ruan zhu\DeepLearnToolbox\EMDDBN\package_emd\EMDs\emd.m, 22275 , 2015-03-11
ruan zhu\DeepLearnToolbox\EMDDBN\package_emd\EMDs\emdc.m, 2280 , 2015-03-11
ruan zhu\DeepLearnToolbox\EMDDBN\package_emd\EMDs\emdc_fix.m, 2141 , 2015-03-11

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发表评论

0 个回复

  • ssb_mod_01
    移相法生成单边带调制信号，对m(t)=sinc^2(t)函数构成的基带信号进行单边带调制,接收端相干解调低通滤波。(ssb_mod_01.m- phase shift method to generate the single sideband modulation signal m (t) = the sinc ^ 2 (t) function constitute the base band signal performs single sideband modulation, the receiving terminal Coherent Solutions of low pass filtering)
    2012-09-14 11:18:31下载
    积分：1
  • Bayesian-Vector-Autoregression-using-Bayesian-est
    Bayesian Vector Autoregression using Bayesian estimation method
    2015-02-16 10:02:18下载
    积分：1
  • pv_array
    来源于国外论文，可以生成pv曲线，亲测有用(Papers abroad, you can generate pv curve, pro-test useful)
    2015-03-11 21:32:21下载
    积分：1
  • OFDM
    OFDM原理国外解释详细文档。及matlab实现。有时域、频域、相位、功率谱等图参照。(OFDM Principles of documents abroad, a more detailed explanation. And matlab implementation. Sometimes domain, frequency domain, phase, power spectra map reference.)
    2010-01-16 10:12:59下载
    积分：1
  • imageconvert
    根据图像的灰度对图像进行分割，实现目标的提取(According to the image gray level image segmentation)
    2011-05-17 16:46:05下载
    积分：1
  • quyuzengzhang
    一种基于区域增长的图像分割方法，代码实现比较简单。(An image segmentation method based on regional growth, the code is relatively simple.)
    2012-05-21 20:19:57下载
    积分：1
  • Fourier-transform
    傅 立叶变换是数字信号处理领域一种很重要的算法。要知道傅立叶变换算法的 意义，首先要了解傅立叶原理的意义。傅立叶原理表明：任何连续测量的时序或 信号，都 可以表示为不同频率的正弦波信号的无限叠加。而根据该原理创立的 傅立叶变换算法利用直接测量到的原始信号，以累加方式来计算该信号中不同正 弦波信号的频 率、振幅和相位。 (The goals for the course are to gain a facility with using the Fourier transform, both specific techniques and general principles, and learning to recognize when, why, and how it is used. Together with a great variety, the subject also has a great coherence, and the hope is students come to appreciate both. )
    2011-12-09 16:15:10下载
    积分：1
  • program
    说明：  这是一个函数图像的源代码，用matlab编程的(function graph)
    2009-08-09 19:26:42下载
    积分：1
  • chuanghanshu
    信号被窗函数截断，并做频谱分析，比较汉宁窗、三角窗等的特点(Window function signal is cut off, and do spectral analysis, comparing Hanning, triangular windows and other characteristics)
    2013-08-22 17:14:23下载
    积分：1
  • wavelet
    源码是MATLAB7.0在图像处理中的应用这本书中的应用实例一：小波图像分解与合成，有关haar小波的，主程序中需要做少许改动运行会成功（可以参照书来改动）。(Source is MATLAB7.0 in the image processing application example in this book I: Wavelet image decomposition and synthesis, the haar wavelet, the main program needs to be done a little change in the run will be successful (you can refer to the book to change).)
    2010-06-17 21:14:29下载
    积分：1
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