A Comparative Study of Training Algorithms of Artificial Neural Network using MATLAB

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IJCA Proceedings on Technical Symposium on Emerging Technologies in Computer Science
© 2016 by IJCA Journal
TSETCS 2016 - Number 2
Year of Publication: 2016
Authors:
Saumya Verma
Vaishnavi Gupta
Devraj Kamboj

Saumya Verma, Vaishnavi Gupta and Devraj Kamboj. Article: A Comparative Study of Training Algorithms of Artificial Neural Network using MATLAB. IJCA Proceedings on Technical Symposium on Emerging Technologies in Computer Science TSETCS 2016(2):13-19, June 2016. Full text available. BibTeX

@article{key:article,
	author = {Saumya Verma and Vaishnavi Gupta and Devraj Kamboj},
	title = {Article: A Comparative Study of Training Algorithms of Artificial Neural Network using MATLAB},
	journal = {IJCA Proceedings on Technical Symposium on Emerging Technologies in Computer Science},
	year = {2016},
	volume = {TSETCS 2016},
	number = {2},
	pages = {13-19},
	month = {June},
	note = {Full text available}
}

Abstract

Neural networks are simplified models of the biological neuron system. A neural network is a massively parallel distributed system made up of highly interconnected neural computing elements that have the ability to learn and thereby acquire knowledge and make it available for use. ANN's, like people, learn by example. This paper gives overview of artificial neural networks, their working, architecture, learning methods, how one can create and train their own neural network using MATLAB, and their applications.

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