Artificial Neural Networks

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Citation (Scopus)

Abstract

Artificial Neural Networks (ANNs) are computational methods that belong to the field of Machine Learning [Mitchell, 1997, Kelleher et al., 2015, Gabriel, 2016]. The aim of ANNs is to implement a very simplified model of the human brain. In this way, ANNs try to learn tasks (to solve problems) mimicking the behavior of the brain. The brain is composed of a large set of specialized cells, called neurons. Each single neuron is, in itself, a very simple entity, and the power of the brain is given by the fact that neurons are numerous and strongly interconnected, by means of connections called synapses. The brain learns because neurons are able to communicate with each other. A picture of a biological neuron and its synapses is shown in Figure 7.1. Biological neurons can receive stimuli and, as a consequence, emit (electric) signals, which can stimulate other neurons. When a biological neuron emits its signal, we say that it “fires”.

Original languageEnglish
Title of host publicationLectures on Intelligent Systems
PublisherSpringer, Cham
Pages161-204
Number of pages44
ISBN (Electronic)978-3-031-17922-8
ISBN (Print)978-3-031-17921-1, 978-3-031-17924-2
DOIs
Publication statusPublished - 13 Jan 2023

Publication series

NameNatural Computing Series
ISSN (Print)1619-7127

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