Fast Linear Adaptive Skipping Training Algorithm for Training Artificial Neural Network
Joint Authors
Manjula Devi, R.
Kuppuswami, S.
Suganthe, R. C.
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-06-25
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Artificial neural network has been extensively consumed training model for solving pattern recognition tasks.
However, training a very huge training data set using complex neural network necessitates excessively high training time.
In this correspondence, a new fast Linear Adaptive Skipping Training (LAST) algorithm for training artificial neural network (ANN) is instituted.
The core essence of this paper is to ameliorate the training speed of ANN by exhibiting only the input samples that do not categorize perfectly in the previous epoch which dynamically reducing the number of input samples exhibited to the network at every single epoch without affecting the network’s accuracy.
Thus decreasing the size of the training set can reduce the training time, thereby ameliorating the training speed.
This LAST algorithm also determines how many epochs the particular input sample has to skip depending upon the successful classification of that input sample.
This LAST algorithm can be incorporated into any supervised training algorithms.
Experimental result shows that the training speed attained by LAST algorithm is preferably higher than that of other conventional training algorithms.
American Psychological Association (APA)
Manjula Devi, R.& Kuppuswami, S.& Suganthe, R. C.. 2013. Fast Linear Adaptive Skipping Training Algorithm for Training Artificial Neural Network. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1009086
Modern Language Association (MLA)
Manjula Devi, R.…[et al.]. Fast Linear Adaptive Skipping Training Algorithm for Training Artificial Neural Network. Mathematical Problems in Engineering No. 2013 (2013), pp.1-9.
https://search.emarefa.net/detail/BIM-1009086
American Medical Association (AMA)
Manjula Devi, R.& Kuppuswami, S.& Suganthe, R. C.. Fast Linear Adaptive Skipping Training Algorithm for Training Artificial Neural Network. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-9.
https://search.emarefa.net/detail/BIM-1009086
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009086