Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications
Ullah S, Koravuna S, Rückert U, Jungeblut T (2023)
Frontiers in Computational Neuroscience 17.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
Download
fncom-17-1215824.pdf
2.27 MB
Einrichtung
Abstract / Bemerkung
This article presents a comprehensive analysis of spiking neural networks (SNNs) and their mathematical models for simulating the behavior of neurons through the generation of spikes. The study explores various models, includingLIFandNLIF, for constructing SNNs and investigates their potential applications in different domains. However, implementation poses several challenges, including identifying the most appropriate model for classification tasks that demand high accuracy and low-performance loss. To address this issue, this research study compares the performance, behavior, and spike generation of multiple SNN models using consistent inputs and neurons. The findings of the study provide valuable insights into the benefits and challenges of SNNs and their models, emphasizing the significance of comparing multiple models to identify the most effective one. Moreover, the study quantifies the number of spiking operations required by each model to process the same inputs and produce equivalent outputs, enabling a thorough assessment of computational efficiency. The findings provide valuable insights into the benefits and limitations of SNNs and their models. The research underscores the significance of comparing different models to make informed decisions in practical applications. Additionally, the results reveal essential variations in biological plausibility and computational efficiency among the models, further emphasizing the importance of selecting the most suitable model for a given task. Overall, this study contributes to a deeper understanding of SNNs and offers practical guidelines for using their potential in real-world scenarios.
Erscheinungsjahr
2023
Zeitschriftentitel
Frontiers in Computational Neuroscience
Band
17
Urheberrecht / Lizenzen
eISSN
1662-5188
Page URI
https://pub.uni-bielefeld.de/record/2982807
Zitieren
Ullah S, Koravuna S, Rückert U, Jungeblut T. Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications. Frontiers in Computational Neuroscience. 2023;17.
Ullah, S., Koravuna, S., Rückert, U., & Jungeblut, T. (2023). Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications. Frontiers in Computational Neuroscience, 17. https://doi.org/10.3389/fncom.2023.1215824
Ullah, Sana, Koravuna, Shamini, Rückert, Ulrich, and Jungeblut, Thorsten. 2023. “Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications”. Frontiers in Computational Neuroscience 17.
Ullah, S., Koravuna, S., Rückert, U., and Jungeblut, T. (2023). Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications. Frontiers in Computational Neuroscience 17.
Ullah, S., et al., 2023. Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications. Frontiers in Computational Neuroscience, 17.
S. Ullah, et al., “Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications”, Frontiers in Computational Neuroscience, vol. 17, 2023.
Ullah, S., Koravuna, S., Rückert, U., Jungeblut, T.: Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications. Frontiers in Computational Neuroscience. 17, (2023).
Ullah, Sana, Koravuna, Shamini, Rückert, Ulrich, and Jungeblut, Thorsten. “Exploring spiking neural networks: a comprehensive analysis of mathematical models and applications”. Frontiers in Computational Neuroscience 17 (2023).
Alle Dateien verfügbar unter der/den folgenden Lizenz(en):
Creative Commons Namensnennung 4.0 International Public License (CC-BY 4.0):
Volltext(e)
Name
fncom-17-1215824.pdf
2.27 MB
Access Level
Open Access
Zuletzt Hochgeladen
2024-02-08T14:01:59Z
MD5 Prüfsumme
fb04cc96d2654e6f24bfa18f0421c7ff
Daten bereitgestellt von European Bioinformatics Institute (EBI)
Zitationen in Europe PMC
Daten bereitgestellt von Europe PubMed Central.
References
Daten bereitgestellt von Europe PubMed Central.
Export
Markieren/ Markierung löschen
Markierte Publikationen
Web of Science
Dieser Datensatz im Web of Science®Quellen
PMID: 37692462
PubMed | Europe PMC
Suchen in