Basic of Artificial Neural Network

  • Mr Rahul Sehrawat Dronacharya College of Engineering , Gurgaon, Haryana
  • Mr Pankaj Gupta Dronacharya College of Engineering , Gurgaon, Haryana
  • Mr Ravishu Yadav Dronacharya College of Engineering , Gurgaon, Haryana
DOI: https://doi.org/10.53555/cse.v1i5.1262
Keywords: ANN(Artificial Neural Network),, Neurons, pattern recognition

Abstract

An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological
nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the
information processing system. It is composed of a large number of highly interconnected processing elements (neurons)
working in unison to solve specific problems. Artificial neural networks are generally presented as systems of interconnected
neurons which can compute values from inputs, and are capable of machine learning as well as pattern recognition thanks to
their adaptive nature. ANNs, like people, learn by example. Learning in biological systems involves adjustments to the synaptic
connections that exist between the neurons. This is true of ANNs as well. This paper gives overview of Artificial Neural
Network, working & training of ANN. It also explain the application and advantages of ANN.

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Author Biographies

Mr Rahul Sehrawat, Dronacharya College of Engineering , Gurgaon, Haryana

Department of Information Technology
Dronacharya College of Engineering , Gurgaon, Haryana

Mr Pankaj Gupta, Dronacharya College of Engineering , Gurgaon, Haryana

Department of Information Technology
Dronacharya College of Engineering , Gurgaon, Haryana

Mr Ravishu Yadav, Dronacharya College of Engineering , Gurgaon, Haryana

Department of Information Technology
Dronacharya College of Engineering , Gurgaon, Haryana

Published
2015-05-31
How to Cite
Sehrawat, M. R., Gupta, M. P., & Yadav, M. R. (2015). Basic of Artificial Neural Network. IJRDO -Journal of Computer Science Engineering, 1(5), 26-30. https://doi.org/10.53555/cse.v1i5.1262
Issue
Vol. 1 No. 5 (2015): IJRDO - Journal of Computer Science Engineering
Section
Articles

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