Abstract
(Artificial) neural networks are information processing systems, whose structure and operation principles are inspired by the nervous system and the brain of animals and humans. They consist of a large number of fairly simple units, the so-called neurons, which are working in parallel. These neurons communicate by sending information in the form of activation signals, along directed connections, to each other.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The nervous system consists not only of neurons, not even for the largest part. Besides neurons there are various other cells, for instance, the so-called glia cells, which have a supporting function.
References
J.R. Anderson, Cognitive Psychology and its Implications, 4th edn. (Freeman, New York, NY, USA, 1995)
M.A. Boden (ed.), The Philosophy of Artificial Intelligence (Oxford University Press, Oxford, United Kingdom, 1990)
A. Newell, H.A. Simon. Computer Science as Empirical Enquiry: Symbols and Search. Communications of the Association for Computing Machinery 19. Association for Computing Machinery, New York, NY, USA 1976. Reprinted in [Boden 1990], 105–132
Author information
Authors and Affiliations
Corresponding authors
Rights and permissions
Copyright information
© 2016 Springer-Verlag London
About this chapter
Cite this chapter
Kruse, R., Borgelt, C., Braune, C., Mostaghim, S., Steinbrecher, M. (2016). Introduction to Neural Networks. In: Computational Intelligence. Texts in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-7296-3_2
Download citation
DOI: https://doi.org/10.1007/978-1-4471-7296-3_2
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-7294-9
Online ISBN: 978-1-4471-7296-3
eBook Packages: Computer ScienceComputer Science (R0)