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DeepLearnToolbox-master

于 2021-02-27 发布
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代码说明：

说明：  深度学习工具箱，包括BP、CNN、DBN、CAE等多个网络。包含数据可直接运行。(Deep learning toolbox, including multiple networks such as BP, CNN, DBN, CAE, etc. Containing data can be run directly.)

文件列表：

DeepLearnToolbox-master\.travis.yml, 249 , 2018-03-15
DeepLearnToolbox-master\CAE\caeapplygrads.m, 1219 , 2018-03-15
DeepLearnToolbox-master\CAE\caebbp.m, 917 , 2018-03-15
DeepLearnToolbox-master\CAE\caebp.m, 1011 , 2018-03-15
DeepLearnToolbox-master\CAE\caedown.m, 259 , 2018-03-15
DeepLearnToolbox-master\CAE\caeexamples.m, 754 , 2018-03-15
DeepLearnToolbox-master\CAE\caenumgradcheck.m, 3618 , 2018-03-15
DeepLearnToolbox-master\CAE\caesdlm.m, 845 , 2018-03-15
DeepLearnToolbox-master\CAE\caetrain.m, 1148 , 2018-03-15
DeepLearnToolbox-master\CAE\caeup.m, 489 , 2018-03-15
DeepLearnToolbox-master\CAE\max3d.m, 173 , 2018-03-15
DeepLearnToolbox-master\CAE\scaesetup.m, 1937 , 2018-03-15
DeepLearnToolbox-master\CAE\scaetrain.m, 270 , 2018-03-15
DeepLearnToolbox-master\CNN\cnnapplygrads.m, 575 , 2018-03-15
DeepLearnToolbox-master\CNN\cnnbp.m, 2141 , 2018-03-15
DeepLearnToolbox-master\CNN\cnnff.m, 1774 , 2018-03-15
DeepLearnToolbox-master\CNN\cnnnumgradcheck.m, 3430 , 2018-03-15
DeepLearnToolbox-master\CNN\cnnsetup.m, 2020 , 2018-03-15
DeepLearnToolbox-master\CNN\cnntest.m, 193 , 2018-03-15
DeepLearnToolbox-master\CNN\cnntrain.m, 845 , 2018-03-15
DeepLearnToolbox-master\CONTRIBUTING.md, 544 , 2018-03-15
DeepLearnToolbox-master\create_readme.sh, 744 , 2018-03-15
DeepLearnToolbox-master\data\mnist_uint8.mat, 14735220 , 2018-03-15
DeepLearnToolbox-master\DBN\dbnsetup.m, 557 , 2018-03-15
DeepLearnToolbox-master\DBN\dbntrain.m, 232 , 2018-03-15
DeepLearnToolbox-master\DBN\dbnunfoldtonn.m, 425 , 2018-03-15
DeepLearnToolbox-master\DBN\rbmdown.m, 90 , 2018-03-15
DeepLearnToolbox-master\DBN\rbmtrain.m, 1401 , 2018-03-15
DeepLearnToolbox-master\DBN\rbmup.m, 89 , 2018-03-15
DeepLearnToolbox-master\LICENSE, 1313 , 2018-03-15
DeepLearnToolbox-master\NN\nnapplygrads.m, 628 , 2018-03-15
DeepLearnToolbox-master\NN\nnbp.m, 1638 , 2018-03-15
DeepLearnToolbox-master\NN\nnchecknumgrad.m, 704 , 2018-03-15
DeepLearnToolbox-master\NN\nneval.m, 811 , 2018-03-15
DeepLearnToolbox-master\NN\nnff.m, 1849 , 2018-03-15
DeepLearnToolbox-master\NN\nnpredict.m, 192 , 2018-03-15
DeepLearnToolbox-master\NN\nnsetup.m, 1844 , 2018-03-15
DeepLearnToolbox-master\NN\nntest.m, 184 , 2018-03-15
DeepLearnToolbox-master\NN\nntrain.m, 2414 , 2018-03-15
DeepLearnToolbox-master\NN\nnupdatefigures.m, 1858 , 2018-03-15
DeepLearnToolbox-master\README.md, 8861 , 2018-03-15
DeepLearnToolbox-master\README_header.md, 2244 , 2018-03-15
DeepLearnToolbox-master\REFS.md, 950 , 2018-03-15
DeepLearnToolbox-master\SAE\saesetup.m, 132 , 2018-03-15
DeepLearnToolbox-master\SAE\saetrain.m, 308 , 2018-03-15
DeepLearnToolbox-master\tests\runalltests.m, 165 , 2018-03-15
DeepLearnToolbox-master\tests\test_cnn_gradients_are_numerically_correct.m, 552 , 2018-03-15
DeepLearnToolbox-master\tests\test_example_CNN.m, 981 , 2018-03-15
DeepLearnToolbox-master\tests\test_example_DBN.m, 1031 , 2018-03-15
DeepLearnToolbox-master\tests\test_example_NN.m, 3247 , 2018-03-15
DeepLearnToolbox-master\tests\test_example_SAE.m, 934 , 2018-03-15
DeepLearnToolbox-master\tests\test_nn_gradients_are_numerically_correct.m, 749 , 2018-03-15
DeepLearnToolbox-master\util\allcomb.m, 2618 , 2018-03-15
DeepLearnToolbox-master\util\expand.m, 1958 , 2018-03-15
DeepLearnToolbox-master\util\flicker.m, 208 , 2018-03-15
DeepLearnToolbox-master\util\flipall.m, 80 , 2018-03-15
DeepLearnToolbox-master\util\fliplrf.m, 543 , 2018-03-15
DeepLearnToolbox-master\util\flipudf.m, 576 , 2018-03-15
DeepLearnToolbox-master\util\im2patches.m, 313 , 2018-03-15
DeepLearnToolbox-master\util\isOctave.m, 108 , 2018-03-15
DeepLearnToolbox-master\util\makeLMfilters.m, 1895 , 2018-03-15
DeepLearnToolbox-master\util\myOctaveVersion.m, 169 , 2018-03-15
DeepLearnToolbox-master\util\normalize.m, 97 , 2018-03-15
DeepLearnToolbox-master\util\patches2im.m, 242 , 2018-03-15
DeepLearnToolbox-master\util\randcorr.m, 283 , 2018-03-15
DeepLearnToolbox-master\util\randp.m, 2083 , 2018-03-15
DeepLearnToolbox-master\util\rnd.m, 49 , 2018-03-15
DeepLearnToolbox-master\util\sigm.m, 48 , 2018-03-15
DeepLearnToolbox-master\util\sigmrnd.m, 126 , 2018-03-15
DeepLearnToolbox-master\util\softmax.m, 256 , 2018-03-15
DeepLearnToolbox-master\util\tanh_opt.m, 54 , 2018-03-15
DeepLearnToolbox-master\util\visualize.m, 1072 , 2018-03-15
DeepLearnToolbox-master\util\whiten.m, 183 , 2018-03-15
DeepLearnToolbox-master\util\zscore.m, 137 , 2018-03-15
DeepLearnToolbox-master\说明.docx, 15054 , 2018-03-15
DeepLearnToolbox-master\CAE, 0 , 2020-09-29
DeepLearnToolbox-master\CNN, 0 , 2020-09-29
DeepLearnToolbox-master\data, 0 , 2020-09-29
DeepLearnToolbox-master\DBN, 0 , 2020-09-29
DeepLearnToolbox-master\NN, 0 , 2020-09-29
DeepLearnToolbox-master\SAE, 0 , 2020-09-29
DeepLearnToolbox-master\tests, 0 , 2020-09-29
DeepLearnToolbox-master\util, 0 , 2020-09-29
DeepLearnToolbox-master, 0 , 2020-09-29

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发表评论

0 个回复

  • finger
    指纹识别的一个小例子，很不错的。 使用matlab编写的，里面一个具体的指纹图片被识别了。(Fingerprint identification of a small example, it is good. Prepared to use matlab, inside a concrete picture of the fingerprint was identified.)
    2008-04-16 16:21:10下载
    积分：1
  • particle_filter
    粒子滤波例程，用于无杂波环境下的目标跟踪。(Particle filter routines for non-target tracking in clutter.)
    2010-05-29 09:21:40下载
    积分：1
  • emwork2_6_1
    海伦法计算偶极天线电流分布，增益，并与解析法，波克林顿法比较(Helen dipole antenna current distribution method, gain, and with the analytical method, wave Clinton Comparison)
    2010-06-01 12:25:06下载
    积分：1
  • MMUSIC
    利用经典MUSIC算法及MMUSIC算法估计波达方向，绝对可运行！程序没错误！(Using the classical MUSIC algorithm and MMUSIC algorithm to estimate DOA, absolutely can run! Program did not wrong!)
    2021-04-28 17:08:43下载
    积分：1
  • 3MATLABYUYIN
    3.1语音信号的同态处理和倒谱分析30 3.1.1同态处理的基本原理30 3.1.2复倒谱和倒谱31 3.2离散余弦变换34 3.3Mel频率倒谱系数的分析37 3.3.1Mel滤波器组37 3.3.2MFCC特征参数提取38 3.4小波和小波包变换43 3.4.1小波变换43 3.4.2小波包变换44 3.4.3小波包算法45 3.4.4MATLAB中一维小波和小波包变换函数46 3.4.5MATLAB语音信号小波和小波包变换的例子49 3.5EMD的基本理论和算法53 3.5.1EMD的基本概念53 3.5.2EMD 的基本原理55 3.5.3EMD法的完备性和正交性57 3.5.4基于EMD的Hilbert变换的基本原理和算法59 3.5.5EMD法的MATLAB函数60(3.1 homomorphic speech signal processing fundamentals and cepstrum analysis 30 3.1.1 30 3.1.2 homomorphic processing complex cepstrum and cepstrum 31 3.2 Discrete Cosine Transform 34 3.3Mel frequency analysis of 37 3.3.1Mel cepstral filtering control group of 37 3.3.2MFCC feature extraction 38 3.4 wavelet and wavelet packet transform wavelet transform 43 43 3.4.1 3.4.2 3.4.3 44 wavelet packet transform wavelet packet algorithm 45 3.4.4MATLAB one-dimensional wavelet and wavelet packet transform function 46 3.4.5MATLAB voice signal example of wavelet and wavelet packet transform 49 3.5EMD basic theory and algorithms 53 3.5.1EMD basic concepts of the basic principles of law 53 3.5.2EMD of 55 3.5.3EMD completeness and orthogonality 57 3.5.4 Based on the basic principle of MATLAB functions and algorithms EMD Hilbert transform 60 of 59 3.5.5EMD law)
    2021-05-14 02:30:02下载
    积分：1
  • CABCA_PID
    The Matlab Code present the development of an intelligent PID controller using Cultural Artificial Bee Colony Algorithm CABCA. The Normative and situational Knowledge in cultural algorithm were first used to guide the evolution and direction of ABC. thereafter the develop controller was used in the position control of DC motor.
    2016-03-23 00:20:57下载
    积分：1
  • 3
    说明：  随机数生成程序，用于作为系统辨识的输入信号，得出相应的输出(Random number generator procedure for system identification as an input signal, the output reached)
    2009-05-03 18:14:13下载
    积分：1
  • Forward-kinematics
    机械臂正运动学，工作空间,包括5个文件，kongjian.m为运行文件，R_x.m为绕x轴转动变换矩阵，T_m.m为平移变换矩阵(Forward kinematics workspace)
    2020-12-30 17:09:00下载
    积分：1
  • ofdm-tongbusuanfa
    OFDM载波同步算法的研究，验证后顺利运行，仿真效果好(After the OFDM carrier synchronization algorithm research, validation run smoothly, good simulation effect)
    2016-04-27 08:09:35下载
    积分：1
  • somefilter
    设计的带通滤波器方法 改变参数就行了 里面有几种方法(designed band pass filter change of parameters on a trip inside there are several ways)
    2007-05-22 00:35:17下载
    积分：1
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