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Backpropagation
Known as:
Error back-propagation
, Backpropogation
, Back prop
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Backpropagation, an abbreviation for "backward propagation of errors", is a common method of training artificial neural networks used in conjunction…
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Related topics
Related topics
50 relations
AI winter
ALOPEX
AdaBoost
Autoencoder
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Papers overview
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Highly Cited
2009
Highly Cited
2009
Future Generation Information Technology, First International Conference, FGIT 2009, Jeju Island, Korea, December 10-12, 2009. Proceedings
Fgit
,
Young-hoon Lee
Future Generation Information Technology
2009
Corpus ID: 41829986
Keynotes.- Computer Science: Where Is the Next Frontier?.- Video Forgery.- Data Analysis, Data Processing, Advanced Computation…
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2008
2008
Automated Textile Defect Recognition System Using Computer Vision and Artificial Neural Networks
Atiqul Islam
,
Shamim Akhter
,
Tumnun E. Mursalin
2008
Corpus ID: 6616660
Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing…
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1997
1997
AN OBJECTIVE-GUIDED ORTHO-SYNAPSE HOPFIELD NETWORK APPROACH TO MACHINE GROUPING PROBLEMS
S. Ri
,
M. Liang
1997
Corpus ID: 58346957
This paper reports an ortho-synapse Hopfield network (OSHN) for solving machine grouping problems. An objective-guided search…
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1997
1997
Development of Both Linear and Nonlinear Methods To Predict the Liquid Viscosity at 20 C of Organic Compounds
Takahiro Suzuki
,
R. Ebert
,
G. Schüürmann
Journal of chemical information and computer…
1997
Corpus ID: 34522145
Experimental values for the liquid viscosity (η) at 20 °C ranging from 0.164 mPa·s (trans-2-pentene) to 1490 mPa·s (glycerol…
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1997
1997
A Neurocomputing Controller for Bandwith Allocation in ATM Networks
S. Youssef
,
I. Habib
,
T. Saadawi
IEEE J. Sel. Areas Commun.
1997
Corpus ID: 21877372
We propose a new neurocomputing call admission control (CAC) algorithm for asynchronous transfer mode (ATM) networks. The…
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1997
1997
Figure 4. Typical Evolution of a Population of Networks Generated by (a) Mta Algorithm, (b) Cca Algorithm and (c) Ccas Algorithm. (a) (b) 6. Acknowledgments 7. References
J. Vandewalle
1997
Corpus ID: 61573199
[4] F. Dellaert, and J. Vandewalle, " Automatic design of cellular neural networks by means of genetic algorithms: finding a…
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1995
1995
Comments on "Noise injection into inputs in back propagation learning"
Yves Grandvalet
,
S. Canu
IEEE Transactions on Systems, Man and Cybernetics
1995
Corpus ID: 206401542
The generalization capacity of neural networks learning from examples is important. Several authors showed experimentally that…
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Highly Cited
1993
Highly Cited
1993
Prediction of boiling points of organic heterocyclic compounds using regression and neural network techniques
L. M. Egolf
,
P. Jurs
Journal of chemical information and computer…
1993
Corpus ID: 21861676
High quality models which relate structural descriptors to normal boiling points have been developed for large, diverse groups of…
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Highly Cited
1993
Highly Cited
1993
A fuzzy neural network learning fuzzy control rules and membership functions by fuzzy error backpropagation
D. Nauck
,
R. Kruse
IEEE International Conference on Neural Networks
1993
Corpus ID: 58070646
A kind of neural network architecture designed for control tasks is presented. It is called the fuzzy neural network. The…
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1990
1990
Multi-layer perceptrons with discrete weights
M. Marchesi
,
G. Orlandi
,
F. Piazza
,
L. Pollonara
,
A. Uncini
IJCNN International Joint Conference on Neural…
1990
Corpus ID: 45762431
The feasibility of restricting the weight values in multilayer perceptrons to powers of two or sums of powers of two is studied…
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