The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Comprehensive Study on Architecture of Neural Networks and Its Prospects in Cognitive Computing
|
|
Author(s): Sushree Bibhuprada B. Priyadarshini (Institute of Technical Education and Research, India)
Copyright: 2020
Volume: 11
Issue: 2
Pages: 19
Source title:
International Journal of Synthetic Emotions (IJSE)
DOI: 10.4018/IJSE.2020070103
Purchase
|
Abstract
This paper proffers an overview of neural network, coupled with early neural network architecture, learning methods, and applications. Basically, neural networks are simplified models of biological nervous systems and that's why they have drawn crucial attention of research community in the domain of artificial intelligence. Basically, such networks are highly interconnected networks possessing a huge number of processing elements known as neurons. Such networks learn by examples and exhibit the mapping capabilities, generalization, fault resilience conjointly with escalated rate of information processing. In the current paper, various types of learning methods employed in case of neural networks are discussed. Subsequently, the paper details the deep neural network (DNN), its key concepts, optimization strategies, activation functions used. Afterwards, logistic regression and conventional optimization approaches are described in the paper. Finally, various applications of neural networks in various domains are included in the paper before concluding it.
Related Content
|
Rana Seif Fathalla, Wafa Saad Alshehri.
© 2020.
16 pages.
|
|
Adel Alti.
© 2020.
10 pages.
|
|
Sandip Palit, Soumadip Ghosh.
© 2020.
9 pages.
|
|
Amiya Bhusan Bagjadab, Sushree Bibhuprada B. Priyadarshini.
© 2020.
13 pages.
|
|
Soumadip Ghosh, Arnab Hazra, Abhishek Raj.
© 2020.
9 pages.
|
|
Rana Fathalla.
© 2020.
18 pages.
|
|
Umesh Kokate, Arviand V. Deshpande, Parikshit N. Mahalle.
© 2020.
18 pages.
|
|
|