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Published on 19 March 2024
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Chen,A. (2024). Artificial intelligence in analogue circuit design. Applied and Computational Engineering,48,181-185.
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Artificial intelligence in analogue circuit design

Ao Chen *,1,
  • 1 University of Warwick

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/48/20241365

Abstract

Analog circuit design plays an integral part in modern society; however, traditional approaches often fall short in terms of efficiency and effectiveness. This paper explores the application and challenges presented by artificial intelligence (AI) technologies in analog circuit design. The objective of this paper was to evaluate the capacity of artificial intelligence technologies such as machine learning, deep learning and reinforcement learning to advance circuit modeling, optimization and layout design processes. A comprehensive literature review and analysis were performed. The study finds that while AI can make significant contributions to circuit design, several challenges must first be overcome. These include data scarcity for training AI models and the opaque nature of AI decisions which prevent their widespread acceptance. Finally, future research directions such as creating synthetic data or developing more interpretable AI models were identified as potential future research avenues.

Keywords

Artificial Intelligence (AI), Analog Circuit Design, Machine Learning (ML), Deep Learning (DL), Circuit Modeling

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Cite this article

Chen,A. (2024). Artificial intelligence in analogue circuit design. Applied and Computational Engineering,48,181-185.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 4th International Conference on Signal Processing and Machine Learning

Conference website: https://www.confspml.org/
ISBN:978-1-83558-336-4(Print) / 978-1-83558-338-8(Online)
Conference date: 15 January 2024
Editor:Marwan Omar
Series: Applied and Computational Engineering
Volume number: Vol.48
ISSN:2755-2721(Print) / 2755-273X(Online)

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