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2019 | OriginalPaper | Chapter

4. Methods of Spiking Neural Networks

Author : Nikola K. Kasabov

Published in: Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Publisher: Springer Berlin Heidelberg

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Abstract

Spiking neural networks (SNN) are biologically inspired ANN where information is represented as binary events (spikes), similar to the event potentials in the brain, and learning is also inspired by principles in the brain. SNN are also universal computational mechanisms (Maass in Math Found Comput Sci 1998, 72–83, 1998 [1]). These and many other reasons that are discussed in this chapter make SNN a preferred computational paradigm for modelling temporal and spatio-temporal data and for building brain-inspired AI. This chapter gives the background information for SNN that is further used in the rest of the book.

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previous chapter Deep Learning and Deep Knowledge Representation in the Human Brain

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Title: Methods of Spiking Neural Networks
Author: Nikola K. Kasabov
Publisher: Springer Berlin Heidelberg
Book: Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence
Print ISBN: 978-3-662-57713-4

Electronic ISBN: 978-3-662-57715-8

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-662-57715-8_4

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