Semantic Communications
暫譯: 語意通信
Chen, Wei, Qin, Zhijin
- 出版商: Springer
- 出版日期: 2026-06-02
- 售價: $4,610
- 貴賓價: 9.5 折 $4,379
- 語言: 英文
- 頁數: 196
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3032110041
- ISBN-13: 9783032110046
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相關分類:
DeepLearning
海外代購書籍(需單獨結帳)
商品描述
This textbook provides a comprehensive, step-by-step guide to Semantic Communications, focusing on how deep learning enhances its performance in modern communication systems. The purpose of the book is to offer students, researchers, and engineers a solid understanding of the theoretical principles and practical applications of semantic communication. The text builds from foundational concepts to advanced topics, making it suitable for graduate-level courses and beyond, while also serving as a reference for professionals looking to incorporate semantic communication into real-world systems. By moving beyond conventional data transmission to focus on meaning and intent, this textbook highlights how AI and deep learning are revolutionizing joint source-channel coding, bandwidth optimization, and task-oriented communications. With a strong emphasis on 6G and next-generation networks, this book offers a comprehensive guide to the theoretical foundations and practical applications of semantic communication, making it an essential resource for researchers, students, and professionals shaping the future of AI-driven telecommunications. The book features discussion questions, MATLAB or Python code for experiments and simulations related to semantic communication systems, PowerPoint slides for instructors, and a solutions manual.
- Combines theoretical principles with practical implementations of semantic communication systems; Addresses the foundational concepts and the hands-on application of deep learning to improve communication efficiency; Features discussion questions, MATLAB code for experiments, PowerPoint slides for instructors, and a solutions manual.
商品描述(中文翻譯)
這本教科書提供了一個全面的逐步指南，專注於語意通信（Semantic Communications），並探討深度學習如何提升其在現代通信系統中的性能。本書的目的是為學生、研究人員和工程師提供對語意通信的理論原則和實際應用的扎實理解。文本從基礎概念開始，逐步深入到高級主題，適合研究生課程及以上，同時也可作為專業人士在實際系統中整合語意通信的參考資料。通過超越傳統數據傳輸，專注於意義和意圖，本教科書突顯了人工智慧（AI）和深度學習如何徹底改變聯合源通道編碼、頻寬優化和任務導向通信。該書強調6G及下一代網絡，提供語意通信的理論基礎和實際應用的全面指南，成為研究人員、學生和專業人士塑造AI驅動電信未來的重要資源。本書包含討論問題、與語意通信系統相關的MATLAB或Python實驗和模擬代碼、供教師使用的PowerPoint簡報以及解答手冊。
- 結合語意通信系統的理論原則與實際實現；
- 涉及基礎概念及深度學習在提高通信效率方面的實際應用；
- 包含討論問題、實驗用的MATLAB代碼、供教師使用的PowerPoint簡報以及解答手冊。
作者簡介
Wei Chen is a Professor at Beijing Jiaotong University, China. He received the B.Eng. degree and M.Eng. degree from Beijing University of Posts and Telecommunications, China, in 2006 and 2009, respectively, and the Ph.D. degree in Computer Science from the University of Cambridge, UK, in 2013. Later, he was a Research Associate with the Computer Laboratory, University of Cambridge from 2013 to 2016. His current research interests include semantic communications, AL/ML for PHY and sparse signal processing. He was a recipient of the 2013 IET Wireless Sensor Systems Premium Award, the 2017 International Conference on Computer Vision (ICCV) Young Researcher Award, the 2019 CCF-Tencent Rhino Bird Innovation Award, the 2020 IWCMC 5G-EWNAT Workshop Best Paper Award, and 2023 IEEE/CIC ICCC Best Paper Award. He has served as the editor and symposium chair of several IEEE/IET journals and international conferences. Recently, he serves as the lead guest editor for IEEE JSTSP Special Issue on Intelligent Signal Processing and Learning for Next Generation Multiple Access.
Zhijin Qin is an Associate Professor at Tsinghua University, China. She was with Queen Mary University of London and Lancaster University as a lecturer as well as with Imperial College London as a research associate from 2016 to 2022. She obtained her PhD degree in 2016 and the bachelor degree in 2012. Her research interests include semantic communications and sparse signal processing in wireless communications. She serves as an area editor of IEEE JSAC Series on Machine learning in Communications and Networks, an associate editor of IEEE Transactions on Communications, IEEE Transactions on Cognitive Communications and Networking, and IEEE Communications Letters. Dr Qin has served as the symposium co-chair for IEEE VTC Fall 2019 and IEEE Globecom 2020/2021. She received the 2017 IEEE Globecom Best Paper Award, the 2018 IEEE Signal Processing Society Young Author Best Paper Award, the 2021 IEEE Communications Society SPCC Early Achievement Award, the 2022 IEEE Communications Society Fred W. Ellersick Prize, the 2023 IEEE ICC Best Paper Award, and 2023 IEEE Signal Processing Society Best Paper Award.
作者簡介(中文翻譯)
陳偉是中國北京交通大學的教授。他於2006年和2009年分別獲得中國北京郵電大學的工程學士學位和工程碩士學位，並於2013年獲得英國劍橋大學的計算機科學博士學位。隨後，他於2013年至2016年擔任劍橋大學計算機實驗室的研究助理。他目前的研究興趣包括語義通信、物理層的人工智慧/機器學習（AL/ML）和稀疏信號處理。他曾獲得2013年IET無線傳感器系統優秀獎、2017年國際計算機視覺會議（ICCV）青年研究者獎、2019年CCF-騰訊犀牛鳥創新獎、2020年IWCMC 5G-EWNAT研討會最佳論文獎，以及2023年IEEE/CIC ICCC最佳論文獎。他曾擔任多本IEEE/IET期刊和國際會議的編輯及研討會主席。最近，他擔任IEEE JSTSP關於下一代多重接入的智能信號處理與學習特刊的主編。
秦志瑾是中國清華大學的副教授。她曾於2016年至2022年在倫敦女王瑪麗大學和蘭卡斯特大學擔任講師，並在倫敦帝國學院擔任研究助理。她於2016年獲得博士學位，2012年獲得學士學位。她的研究興趣包括無線通信中的語義通信和稀疏信號處理。她擔任IEEE JSAC系列關於通信和網絡中的機器學習的區域編輯，以及IEEE通信學報、IEEE認知通信與網絡學報和IEEE通信信函的副編輯。秦博士曾擔任2019年IEEE VTC秋季會議和2020/2021年IEEE Globecom的研討會共同主席。她獲得2017年IEEE Globecom最佳論文獎、2018年IEEE信號處理學會青年作者最佳論文獎、2021年IEEE通信學會SPCC早期成就獎、2022年IEEE通信學會Fred W. Ellersick獎、2023年IEEE ICC最佳論文獎，以及2023年IEEE信號處理學會最佳論文獎。
