國立虎尾科技大學 |

Efficient analog integrated circuit sizing with GenAI = exploring generative diffusion models /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Efficient analog integrated circuit sizing with GenAI/ by Pedro H. M. Eid ... [et al.].
其他題名:	exploring generative diffusion models /
其他作者:	Eid, Pedro H. M.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xvii, 78 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Analog integrated circuits - Computer-aided design. -
電子資源:	https://doi.org/10.1007/978-3-031-87105-4
ISBN:	9783031871054

Efficient analog integrated circuit sizing with GenAI = exploring generative diffusion models /
Efficient analog integrated circuit sizing with GenAIexploring generative diffusion models /[electronic resource] :by Pedro H. M. Eid ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xvii, 78 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in applied Sciences and technology. Computational intelligence,2625-3712. - SpringerBriefs in applied Sciences and technology.Computational intelligence..

1 -- Introduction -- 2. State-of-the-art -- 3. Proposed Architectures -- 4. Model Implementation and Optimization -- 5. Experimental Results -- 6. Conclusion and Future Works.

This book focuses on the automation of analog integrated circuit design, particularly the sizing process. It introduces an innovative approach leveraging generative artificial intelligence, specifically denoising diffusion probabilistic models (DDPM). The proposed methodology provides a robust solution for generating circuit designs that meet specific performance constraints, offering a significant improvement over conventional techniques. By integrating advanced machine learning models into the design workflow, the book showcases a transformative way to streamline the process while maintaining accuracy and reliability.

ISBN: 9783031871054

Standard No.: 10.1007/978-3-031-87105-4doiSubjects--Topical Terms:

1066527
Analog integrated circuits
--Computer-aided design.

LC Class. No.: TK7874

Dewey Class. No.: 621.3815

Efficient analog integrated circuit sizing with GenAI = exploring generative diffusion models /
LDR:01956nam a2200337 a 4500 001 1161478
003 DE-He213
005 20250407224354.0
006 m d
007 cr nn 008maaau
008 251029s2025 sz s 0 eng d
020 $a 9783031871054 $q (electronic bk.)
020 $a 9783031871047 $q (paper)
024 7 $a 10.1007/978-3-031-87105-4 $2 doi
035 $a 978-3-031-87105-4
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7874
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 621.3815 $2 23
090 $a TK7874 $b .E27 2025
245 0 0 $a Efficient analog integrated circuit sizing with GenAI $h [electronic resource] : $b exploring generative diffusion models / $c by Pedro H. M. Eid ... [et al.].
260 $a Cham : $c 2025. $b Springer Nature Switzerland : $b Imprint: Springer,
300 $a xvii, 78 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs in applied Sciences and technology. Computational intelligence, $x 2625-3712
505 0 $a 1 -- Introduction -- 2. State-of-the-art -- 3. Proposed Architectures -- 4. Model Implementation and Optimization -- 5. Experimental Results -- 6. Conclusion and Future Works.
520 $a This book focuses on the automation of analog integrated circuit design, particularly the sizing process. It introduces an innovative approach leveraging generative artificial intelligence, specifically denoising diffusion probabilistic models (DDPM). The proposed methodology provides a robust solution for generating circuit designs that meet specific performance constraints, offering a significant improvement over conventional techniques. By integrating advanced machine learning models into the design workflow, the book showcases a transformative way to streamline the process while maintaining accuracy and reliability.
650 0 $a Analog integrated circuits $x Computer-aided design. $3 1066527
650 0 $a Analog integrated circuits $x Computer simulation. $3 1488406
650 0 $a Artificial intelligence $x Engineering applications. $3 889372
650 1 4 $a Computational Intelligence. $3 768837
700 1 $a Eid, Pedro H. M. $3 1488404
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
830 0 $a SpringerBriefs in applied Sciences and technology. $p Computational intelligence. $3 1488405
856 4 0 $u https://doi.org/10.1007/978-3-031-87105-4
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)