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Machine learning for semiconductor materials /
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Gupta, Neeraj, editor. Gupta, Rashmi, editor. Yadav, Rekha, editor. Dhariwal, Sandeep, editor. Sarma, Rajkumar, editor. |
| 서명/저자사항 | Machine learning for semiconductor materials /edited by Neeraj Gupta, Rashmi Gupta, Rekha Yadav, Sandeep Dhariwal, Rajkumar Sarma. |
| 발행사항 | Boca Raton : CRC Press, 2026. |
| 형태사항 | 1 online resource (206 pages) : illustrations (black and white). |
| 총서사항 | Emerging materials and technologies |
| 소장본 주기 | Added to collection customer.56279.3 |
| ISBN | 9781040398104 1040398103 9781003508304 1003508308 1040398057 9781040398050 |
| 기타표준부호 | 10.1201/9781003508304doi |
| 기타표준부호 | CIPO000252455 |
| 요약 | Machine Learning for Semiconductor Materials studies recent techniques and methods of machine learning to mitigate the use of technology computer-aided design (TCAD). It provides various algorithms of machine learning, such as regression, decision tree, support vector machine, K-means clustering and so forth. This book also highlights semiconductor materials and their uses in multi-gate devices and the analog and radio-frequency (RF) behaviours of semiconductor devices with different materials.Features: Focuses on semiconductor materials and the use of machine learning to facilitate understanding and decision-making Covers RF and noise analysis to formulate the frequency behaviour of semiconductor devices at high frequency Explores pertinent biomolecule detection methods Reviews recent methods in the field of machine learning for semiconductor materials with real-life applications Examines the limitations of existing semiconductor materials and steps to overcome the limitations of existing TCAD software This book is aimed at researchers and graduate students in semiconductor materials, machine learning and electrical engineering. |
| 일반주제명 | Machine learning -- Industrial applications. Semiconductors. semiconductor. |
| 언어 | 영어 |
| 기타형태 저록 | Print version:9781032796888 Print version:103279688X9781032796888 |
| 대출바로가기 | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=4229012 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00031132 | 621.381520285631 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |
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