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  Guest Editorial: Special Issue on Learning, Optimization, and Implementation for Circuits and Systems Driven by Artificial Intelligence

Tang, Y., Beerel, P. A., Kurths, J., Chen, G. (2024): Guest Editorial: Special Issue on Learning, Optimization, and Implementation for Circuits and Systems Driven by Artificial Intelligence. - IEEE Transactions on Circuits and Systems I: Regular Papers, 71, 5, 1965-1968.
https://doi.org/10.1109/TCSI.2024.3372789

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 Urheber:
Tang, Yang, Autor
Beerel, Peter A., Autor
Kurths, Jürgen1, Autor              
Chen, Guanrong, Autor
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: Circuits and systems, such as multidimensional and nonlinear ones, large-scale integration circuits, and power networks, play a significant role in the whole spectrum of science and technology, from basic scientific theories to various real-world applications. With the increasing demand from applications, it is vital to develop circuits and systems with high accuracy, stability, flexibility, and security through efficient learning, design optimization, and integrated implementation. The rapid advancement of artificial intelligence (AI) has fostered a symbiotic relationship between circuits and systems and AI in both theory and applications. On the one hand, research in circuits and systems on efficient learning, design optimization, and integrated implementation aided by AI has recently gained a promising development, where energy-efficient circuits and systems have a very broad range of applications. On the other hand, the utilization of AI in real-world applications has become indispensable for the optimization and implementation of circuits and systems with high efficiency and low-power computation. Overall, through advanced learning, optimization, and implementation driven by AI, efficient circuits and systems running in real-time with low power can be realized for wider applications.

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Sprache(n): eng - Englisch
 Datum: 2024-04-292024-05-01
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1109/TCSI.2024.3372789
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Nonlinear Dynamics
Model / method: Machine Learning
MDB-ID: No data to archive
 Art des Abschluß: -

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Titel: IEEE Transactions on Circuits and Systems I: Regular Papers
Genre der Quelle: Zeitschrift, SCI, Scopus
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 71 (5) Artikelnummer: - Start- / Endseite: 1965 - 1968 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/transactions-circuits-systems-regular-papers
Publisher: Institute of Electrical and Electronics Engineers (IEEE)