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Deep Learning Toolbox™
User's Guide
Mark Hudson Beale
Martin T. Hagan
Howard B. Demuth
R2020b
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The MathWorks, Inc.
1 Apple Hill Drive
Natick, MA 01760-2098
Deep Learning Toolbox™ User's Guide
© COPYRIGHT 1992–2020 by The MathWorks, Inc.
The software described in this document is furnished under a license agreement. The software may be used or copied
only under the terms of the license agreement. No part of this manual may be photocopied or reproduced in any form
without prior written consent from The MathWorks, Inc.
FEDERAL ACQUISITION: This provision applies to all acquisitions of the Program and Documentation by, for, or through
the federal government of the United States. By accepting delivery of the Program or Documentation, the government
hereby agrees that this software or documentation qualies as commercial computer software or commercial computer
software documentation as such terms are used or dened in FAR 12.212, DFARS Part 227.72, and DFARS 252.227-7014.
Accordingly, the terms and conditions of this Agreement and only those rights specied in this Agreement, shall pertain
to and govern the use, modication, reproduction, release, performance, display, and disclosure of the Program and
Documentation by the federal government (or other entity acquiring for or through the federal government) and shall
supersede any conicting contractual terms or conditions. If this License fails to meet the government's needs or is
inconsistent in any respect with federal procurement law, the government agrees to return the Program and
Documentation, unused, to The MathWorks, Inc.
Trademarks
MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See
www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be
trademarks or registered trademarks of their respective holders.
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MathWorks products are protected by one or more U.S. patents. Please see www.mathworks.com/patents for
more information.
Revision History
June 1992 First printing
April 1993 Second printing
January 1997 Third printing
July 1997 Fourth printing
January 1998 Fifth printing Revised for Version 3 (Release 11)
September 2000 Sixth printing Revised for Version 4 (Release 12)
June 2001 Seventh printing Minor revisions (Release 12.1)
July 2002 Online only Minor revisions (Release 13)
January 2003 Online only Minor revisions (Release 13SP1)
June 2004 Online only Revised for Version 4.0.3 (Release 14)
October 2004 Online only Revised for Version 4.0.4 (Release 14SP1)
October 2004 Eighth printing Revised for Version 4.0.4
March 2005 Online only Revised for Version 4.0.5 (Release 14SP2)
March 2006 Online only Revised for Version 5.0 (Release 2006a)
September 2006 Ninth printing Minor revisions (Release 2006b)
March 2007 Online only Minor revisions (Release 2007a)
September 2007 Online only Revised for Version 5.1 (Release 2007b)
March 2008 Online only Revised for Version 6.0 (Release 2008a)
October 2008 Online only Revised for Version 6.0.1 (Release 2008b)
March 2009 Online only Revised for Version 6.0.2 (Release 2009a)
September 2009 Online only Revised for Version 6.0.3 (Release 2009b)
March 2010 Online only Revised for Version 6.0.4 (Release 2010a)
September 2010 Online only Revised for Version 7.0 (Release 2010b)
April 2011 Online only Revised for Version 7.0.1 (Release 2011a)
September 2011 Online only Revised for Version 7.0.2 (Release 2011b)
March 2012 Online only Revised for Version 7.0.3 (Release 2012a)
September 2012 Online only Revised for Version 8.0 (Release 2012b)
March 2013 Online only Revised for Version 8.0.1 (Release 2013a)
September 2013 Online only Revised for Version 8.1 (Release 2013b)
March 2014 Online only Revised for Version 8.2 (Release 2014a)
October 2014 Online only Revised for Version 8.2.1 (Release 2014b)
March 2015 Online only Revised for Version 8.3 (Release 2015a)
September 2015 Online only Revised for Version 8.4 (Release 2015b)
March 2016 Online only Revised for Version 9.0 (Release 2016a)
September 2016 Online only Revised for Version 9.1 (Release 2016b)
March 2017 Online only Revised for Version 10.0 (Release 2017a)
September 2017 Online only Revised for Version 11.0 (Release 2017b)
March 2018 Online only Revised for Version 11.1 (Release 2018a)
September 2018 Online only Revised for Version 12.0 (Release 2018b)
March 2019 Online only Revised for Version 12.1 (Release 2019a)
September 2019 Online only Revised for Version 13 (Release 2019b)
March 2020 Online only Revised for Version 14 (Release 2020a)
September 2020 Online only Revised for Version 14.1 (Release 2020b)
Deep Networks
1
Deep Learning in MATLAB ...................................... 1-2
What Is Deep Learning? ...................................... 1-2
Try Deep Learning in 10 Lines of MATLAB Code .................... 1-4
Start Deep Learning Faster Using Transfer Learning ................ 1-5
Train Classiers Using Features Extracted from Pretrained Networks ... 1-6
Deep Learning with Big Data on CPUs, GPUs, in Parallel, and on the Cloud
...................................................... 1-6
Deep Learning with Big Data on GPUs and in Parallel ................ 1-8
Training with Multiple GPUs ................................... 1-9
Deep Learning in the Cloud .................................. 1-10
Fetch and Preprocess Data in Background ....................... 1-10
Pretrained Deep Neural Networks ............................... 1-12
Compare Pretrained Networks ................................ 1-12
Load Pretrained Networks ................................... 1-14
Feature Extraction ......................................... 1-15
Transfer Learning .......................................... 1-15
Import and Export Networks ................................. 1-16
Pretrained Networks for Audio Applications ...................... 1-17
Learn About Convolutional Neural Networks ...................... 1-19
Multiple-Input and Multiple-Output Networks ..................... 1-21
Multiple-Input Networks ..................................... 1-21
Multiple-Output Networks ................................... 1-21
List of Deep Learning Layers ................................... 1-23
Deep Learning Layers ....................................... 1-23
Specify Layers of Convolutional Neural Network ................... 1-31
Image Input Layer ......................................... 1-32
Convolutional Layer ........................................ 1-32
Batch Normalization Layer ................................... 1-36
ReLU Layer .............................................. 1-36
Cross Channel Normalization (Local Response Normalization) Layer ... 1-37
Max and Average Pooling Layers .............................. 1-37
Dropout Layer ............................................ 1-38
Fully Connected Layer ...................................... 1-38
Output Layers ............................................ 1-39
Set Up Parameters and Train Convolutional Neural Network ......... 1-42
Specify Solver and Maximum Number of Epochs .................. 1-42
Specify and Modify Learning Rate ............................. 1-42
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