Cited by 810Neural Networks and ApplicationsNeural dynamics and brain functionMachine Learning and ELM

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Neural Networks

Rojas, Raúl·1996·Springer eBooks

DOI 10.1007/978-3-642-61068-4

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“From these techniques, ANNs is one of the most used and appreciated because it satisfies generalization (Hertz, Krogh, and Palmer 1991; Parekh, Yang, and Honavar 1997) and robustness (Rojas 1996; Freeman and Skapura 1992; Dreyfus et al. 2002).”
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Authors: Rojas, R.
Affiliations: Freie Universität Berlin (DE)
Corresponding author: Rojas, Raúl
ORCID: Rojas, Raúl
Venue: Springer eBooks
Publisher: Springer Berlin Heidelberg
Published: 1996
DOI: 10.1007/978-3-642-61068-4
OpenAlex: W4241395986
Cited by: 810
References: 0
Citations by year: 2026: 15 · 2025: 20 · 2024: 24 · 2023: 40 · 2022: 38 · 2021: 50 · 2020: 47 · 2019: 47 · 2018: 61 · 2017: 51 · 2016: 62 · 2015: 53 · 2014: 49 · 2013: 28 · 2012: 35
FWCI: 1.07
Type: book
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Springer eBooks (publishedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and ELM
Keywords: artificial neural networks, neural network theory, computational model, computing paradigms

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