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語義通信的數學理論 版權信息
- ISBN：9787115659217
- 條形碼：9787115659217 ; 978-7-115-65921-7
- 裝幀：平裝-膠訂
- 冊數：暫無
- 重量：暫無
- 所屬分類：>>
語義通信的數學理論 本書特色
長期以來，由于經 典信息論只研究語法信息，限制了通信科學的進一步發展。近年來，研究語義信息處理與傳輸的通信技術獲得了學術界的普遍關注，語義通信開辟了未來通信技術發展的新方向，但還缺乏一般性的數學指導理論。為了解決這一難題，本書構建了語義信息論的理論框架，對語義信息的度量體系與語義通信的理論極限進行了系統性闡述。
本書內容為張平院士和牛凱教授團隊在語義信息論方面的理論突破，相關成果于2024年6月在《通信學報》首 發，具有很強的前沿性。
語義通信的數學理論 內容簡介
自從1948年經典信息論誕生以來，在其指導下，現代通信技術已經逼近了理論性能極限，例如信息熵，信道容量以及率失真函數。語義通信開辟了未來通信技術發展的新方向，但還缺乏數學指導理論。為了解決這一難題，本文構建了語義信息論的理論框架。通過研究語義通信的機制，我們發現同義性是其基本特征，由此定義了語義信息和語法信息之間的同義映射。基于同義映射這一核心概念，我們引入了語義信息的度量體系，包括語義熵，上/下語義互信息，語義信道容量以及語義率失真函數。進一步，采用隨機編碼以及(聯合)同義典型序列編譯碼方法，證明了三個語義編碼定理，即語義信源編碼定理、語義信道編碼定理以及語義率失真編碼定理。我們發現同義映射擴展了通信系統的極限。進一步討論了連續條件下的語義信息度量。特別地，對于帶寬受限的高斯信道，我們得到了新的信道容量公式，其中平均同義長度表征了信息的辨識能力，這一公式是香農信道容量公式的推廣。綜上所述，本文提出的語義信息論，依據同義映射這一語義信息的本質特征，構建了語義信息的度量體系，引入新的數學工具，證明了語義編碼的基本定理，論證了語義通信系統的性能極限，揭示了未來語義通信的巨大性能潛力。
語義通信的數學理論 目錄
Chapter 1 Introduction 001Chapter 2 Semantic Communication System and Synonymous Mapping 0132.1 Notation Conventions 0132.2 Semantic Communication System 0142.3 Synonymous Mapping 016Chapter 3 Semantic Entropy 0193.1 Semantic Information Measures 019Chapter 1 Introduction 001Chapter 2 Semantic Communication System and Synonymous Mapping 0132.1 Notation Conventions 0132.2 Semantic Communication System 0142.3 Synonymous Mapping 016Chapter 3 Semantic Entropy 0193.1 Semantic Information Measures 0193.2 Semantic Joint Entropy and Semantic Conditional Entropy 022Chapter 4 Semantic Relative Entropy and Mutual Information 0314.1 Semantic Relative Entropy 0314.2 Semantic Mutual Information 036Chapter 5 Semantic Channel Capacity and Semantic Rate-distortion 0415.1 Semantic Channel Capacity 0415.2 Semantic Rate-Distortion 042Chapter 6 Semantic Lossless Source Coding 0456.1 Asymptotic Equipartition Property and Synonymous Typical Set 0456.2 Semantic Source Coding Theorem 0516.3 Semantic Source Coding Method 054Chapter 7 Semantic Channel Coding 0577.1 Jointly Asymptotic Equipartition Property and Jointly Synonymous Typical Set 0577.2 Semantic Channel Coding Theorem 0657.3 Semantic Channel Coding Method 073Chapter 8 Semantic Lossy Source Coding 0818.1 Semantic Distortion and Jointly Typical Set 0818.2 Semantic Rate-Distortion Coding Theorem 085Chapter 9 Semantic Information Measure of Continuous Message 0919.1 Semantic Entropy and Semantic Mutual Information for Continuous Message 0919.2 Semantic Channel Capacity of Gaussian Channel 0989.3 Semantic Channel Capacity of Band-limited Gaussian Channel 1019.4 Semantic Rate-Distortion of Gaussian Source 104Chapter 10 Semantic Joint Source Channel Coding 107Chapter 11 Conclusions 111Appendix 115References 117
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語義通信的數學理論 作者簡介
Kai Niu received the B.S. degree in information engineering and the Ph.D. degree in signal and information processing from Beijing University of Posts and Telecommunications, Beijing, China, in 1998 and 2003, respectively. He is currently a Professor of the School of Artificial Intelligence, Beijing University of Posts and Communications. His research interests include information theory, coding theory, and semantic communication. He has published more than 200 academic papers, and proposed high performance construction algorithm of polar codes applied in 5G standard, and won the first prize of Natural Science of Science and Technology Award of the Chinese Institute of Electronics. Ping Zhang is currently a Professor of the School of Information and Communication Engineering at Beijing University of Posts and Telecommunications, the Director of State Key Laboratory of Networking and Switching Technology, a member of IMT-2020 (5G) Experts Panel, a member of Experts Panel for China’s 6G development. He served as Chief Scientist of National Basic Research Program (973 Program), an expert in Information Technology Division of National High-tech Research and Development program (863 Program), and a member of Consultant Committee on International Cooperation of National Natural Science Foundation of China. His research interests mainly focus on wireless communication. He is an Academician of the Chinese Academy of Engineering (CAE).Kai Niu received the B.S. degree in information engineering and the Ph.D. degree in signal and information processing from Beijing University of Posts and Telecommunications, Beijing, China, in 1998 and 2003, respectively. He is currently a Professor of the School of Artificial Intelligence, Beijing University of Posts and Communications. His research interests include information theory, coding theory, and semantic communication. He has published more than 200 academic papers, and proposed high performance construction algorithm of polar codes applied in 5G standard, and won the first prize of Natural Science of Science and Technology Award of the Chinese Institute of Electronics. Ping Zhang is currently a Professor of the School of Information and Communication Engineering at Beijing University of Posts and Telecommunications, the Director of State Key Laboratory of Networking and Switching Technology, a member of IMT-2020 (5G) Experts Panel, a member of Experts Panel for China’s 6G development. He served as Chief Scientist of National Basic Research Program (973 Program), an expert in Information Technology Division of National High-tech Research and Development program (863 Program), and a member of Consultant Committee on International Cooperation of National Natural Science Foundation of China. His research interests mainly focus on wireless communication. He is an Academician of the Chinese Academy of Engineering (CAE).
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