Advanced Techniques for Optimal Sizing of Analog Integrated Circuits: Quantum Computing, Machine Learning, and Bio-Inspired Optimization
暫譯: 類比積體電路最佳尺寸設計的進階技術：量子計算、機器學習與生物啟發優化
Hoang, Trang, Do, Thinh Quang, Nguyen, Thang Quoc
- 出版商: Wiley
- 出版日期: 2025-10-24
- 售價: $5,080
- 貴賓價: 9.5 折 $4,826
- 語言: 英文
- 頁數: 176
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1394296231
- ISBN-13: 9781394296231
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相關分類:
量子計算、Machine Learning、微電子學 Microelectronics
海外代購書籍(需單獨結帳)
相關主題
商品描述
A novel and authoritative approach to quantum machine learning in integrated circuits design optimization
In Advanced Techniques for Optimal Sizing of Analog Integrated Circuits: Quantum Computing, Machine Learning, and Bio-inspired Optimization, a team of distinguished researchers deliver a comprehensive discussion of the theory, models, methodologies, practical implementation, and utilization of integrated circuit (IC) design. The authors explain IC design optimization, demonstrating cost-effective and time-saving design approaches, as well as techniques likely to be impactful in the near future.
The book covers major topics in the field, describing key concepts, recent advances, effective algorithms, and pressing challenges associated with analog circuit sizing optimization. It discusses using both animal and human-inspired optimization algorithms to create basic and quantum machine learning methods.
Readers will also find:
- A novel approach to quantum machine learning in integrated circuit design optimization
- A range of introductory and advanced topics suitable for students and advanced professionals and researchers
- Detailed illustrations that clarify abstract, complicated engineering concepts
- Complete treatments of animal behavior-inspired optimization algorithms, including particle swarm optimization, firefly algorithm, cuckoo search, bat algorithm
Perfect for researchers in engineering, computer scientists, professors, and senior undergraduate and graduate students in integrated circuit design, this book will also benefit students of machine learning, computer science, quantum computing and optimization.
商品描述(中文翻譯)
一種新穎且權威的量子機器學習在集成電路設計優化中的應用
在模擬集成電路最佳尺寸設計的先進技術：量子計算、機器學習與生物啟發優化一書中，一組傑出的研究者對集成電路（IC）設計的理論、模型、方法論、實際實施及其應用進行了全面的討論。作者解釋了IC設計優化，展示了具有成本效益和節省時間的設計方法，以及在不久的將來可能產生影響的技術。
本書涵蓋了該領域的主要主題，描述了關鍵概念、最近的進展、有效的算法以及與模擬電路尺寸優化相關的緊迫挑戰。它討論了使用動物和人類啟發的優化算法來創建基本的和量子機器學習方法。
讀者還將發現：
- 一種新穎的量子機器學習在集成電路設計優化中的方法
- 適合學生和高級專業人士及研究者的一系列入門和進階主題
- 詳細的插圖，澄清抽象且複雜的工程概念
- 對動物行為啟發的優化算法的完整處理，包括粒子群優化、螢火蟲算法、杜鵑搜索、蝙蝠算法
本書非常適合工程研究人員、計算機科學家、教授以及集成電路設計的高年級本科生和研究生，對於機器學習、計算機科學、量子計算和優化的學生也將大有裨益。
作者簡介
Trang Hoang is an Associate Professor at Ho Chi Minh City University of Technology, Vietnam National University in Ho Chi Minh City in Vietnam.
Thinh Quang Do is a Research Assistant and a PhD student at the Memorial University of Newfoundland, Canada.
Thang Quoc Nguyen is a Research Assistant and a PhD student at the Memorial University of Newfoundland, Canada.
Hoang Trong Nguyen is a Research Assistant and a Master student at the Memorial University of Newfoundland, Canada.
Lihong Zhang is a Full Professor with the Department of Electrical and Computer Engineering, Faculty of Engineering and Applied Science at the Memorial University of Newfoundland, Canada.
Octavia Dobre is a Professor and the Tier-1 Canada Research Chair at Memorial University of Newfoundland, Canada.
Trung Q. Duong is the Canada Excellence Research Chair and a Full Professor at the Memorial University of Newfoundland, Canada. He is also an adjunct professor at Queen's University Belfast, UK and a visiting professor at Kyung Hee University, South Korea.
作者簡介(中文翻譯)
Trang Hoang 是越南胡志明市科技大學的副教授，隸屬於越南國立大學胡志明市分校。
Thinh Quang Do 是加拿大紐芬蘭紀念大學的研究助理及博士生。
Thang Quoc Nguyen 是加拿大紐芬蘭紀念大學的研究助理及博士生。
Hoang Trong Nguyen 是加拿大紐芬蘭紀念大學的研究助理及碩士生。
Lihong Zhang 是加拿大紐芬蘭紀念大學工程與應用科學學院電機與計算機工程系的正教授。
Octavia Dobre 是加拿大紐芬蘭紀念大學的教授及Tier-1加拿大研究主席。
Trung Q. Duong 是加拿大卓越研究主席及加拿大紐芬蘭紀念大學的正教授。他同時也是英國貴族大學的兼任教授及韓國京畿大學的訪問教授。
