Artificial neural networks and learning techniques

Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review


The recent craze for artificial neural networks has spread its roots towards the development of neuroscience, pattern recognition, machine learning and artificial intelligence. The theoretical neuroscience is basically converging towards the basic concept that the brain acts as a complex and decentralized
computer which can perform rigorous calculations in a different approach compared to the conventional digital computers. The motivation behind the study of neural networks is due to their similarity in the structure of the human central nervous system. The elementary processing component of an Artificial
Neural Network (ANN) is called as ‘Neuron’. A large number of neurons interconnected with each other mimic the biological neural network and form an ANN. Learning is an inevitable process that can be used to train an ANN. We can only transfer knowledge to the neural network by the learning procedure.
This chapter presents the detailed concepts of artificial neural networks in addition to some significant aspects on the present research work.
Original languageEnglish
Title of host publicationHandbook of research on advanced computational techniques for simulation-based engineering
EditorsPijush Samui
Place of PublicationHershey PA
PublisherIGI Global Publishing
ISBN (Electronic)9781466694804
ISBN (Print)9781466694798, 1466694793
Publication statusPublished - 2016


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