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

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 Abstract: 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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Language(s): eng - English
 Dates: 2024-04-292024-05-01
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: 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
 Degree: -

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Title: IEEE Transactions on Circuits and Systems I: Regular Papers
Source Genre: Journal, SCI, Scopus
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Pages: - Volume / Issue: 71 (5) Sequence Number: - Start / End Page: 1965 - 1968 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/transactions-circuits-systems-regular-papers
Publisher: Institute of Electrical and Electronics Engineers (IEEE)