{"product_id":"9781394306237","title":"Deep Learning Enabled Semantic Communications","description":"\u003ch1\u003eDeep Learning Enabled Semantic Communications\u003c\/h1\u003e\u003ch3\u003eZhijin Qin | Huiqiang Xie | Zhenzi Weng | Xiaoming Tao\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eTechnology \u0026amp; Engineering \/ Mobile \u0026amp; Wireless Communications\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003e\u003cb\u003eComprehensive overview of the principles, theories, and techniques behind deep learning enabled semantic communications\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003e\u003ci\u003eDeep Learning Enabled Semantic Communications\u003c\/i\u003e explores the synergy between deep learning and semantic communication, particularly in the context of advancing 6G networks. It provides a focused introduction to the subject, systematically covering deep learning enabled semantic communication systems and task-oriented semantic transmission paradigms in wireless communication.  \u003c\/p\u003e\n\u003cp\u003eThe book reviews various aspects of semantic communications, including information theory, multimodal technologies, semantic noise, and semantic sensing. It explores cutting-edge semantic communication architectures, highlighting their advantages over traditional approaches and their potential to drive the future of intelligent information industry. The book also details applications of deep learning-based semantic communication systems across various sources, including text, speech, images, and videos, comprehensively addressing system design, performance optimization, and measurement metrics. \u003c\/p\u003e\n\u003cp\u003eThe book is divided into eight main parts, which cover foundational knowledge, system design, multimodal and multitask-oriented semantic communication systems, joint semantic sensing and sampling, semantic noise suppression, and generative AI enabled systems. \u003c\/p\u003e\n\u003cp\u003eWritten by a diverse group of experts in academia and research institutions, \u003ci\u003eDeep Learning Enabled Semantic Communications \u003c\/i\u003eincludes information on: \u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e Fundamental knowledge about deep learning and semantic communications, including the history, neural networks, and semantic information theory\u003c\/li\u003e\n\u003cli\u003e Compression of multimodal inputs, extraction of global semantic information, and the design of neural networks to boost the capability of handling lengthy speech\u003c\/li\u003e\n\u003cli\u003e Incorporation of different sources to extract semantic features and serve diverse intelligent tasks at the receiver\u003c\/li\u003e\n\u003cli\u003e Introduction of semantic impairments in communications to uncover how to design robust systems\u003c\/li\u003e\n\u003cli\u003e Joint design of data sampling, compression, and coding schemes under the guidance of semantic information\u003c\/li\u003e\n\u003cli\u003e Framework of generative semantic communications to detail the principles of incorporating generative models into semantic communications\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003ci\u003eDeep Learning Enabled Semantic Communications\u003c\/i\u003e is an essential learning resource and reference for graduate and undergraduate students pursuing degrees in wireless communications, signal processing, or deep learning as well as engineers in the telecommunications and IT industries focusing on wireless communication techniques.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e  \u003cp\u003e\u003cb\u003eZhijin Qin\u003c\/b\u003e is an Associate Professor with Tsinghua University, China. She is an Associate Editor for IEEE Transactions on Communications, IEEE Transactions on Cognitive Networking, and IEEE Communications Letters. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eHuiqiang Xie, PhD,\u003c\/b\u003e is an Associate Professor at Jinan University, Guangzhou, Guangdong, China. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eZhenzi Weng\u003c\/b\u003e is a Postdoctoral researcher at Imperial College London, UK. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eXiaoming Tao\u003c\/b\u003e is a Professor with the Department of Electronic Engineering at Tsinghua University. She is also a Senior Member of the IEEE. \u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e17 December 2025\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eWiley-IEEE Press\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9781394306237\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e176\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e16.32\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":44314594148492,"sku":"9781394306237","price":129.56,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781394306237_721d6ea3-ea17-49fb-9703-8bb8521b7787.jpg?v=1780140236","url":"https:\/\/lateknightbooks.com\/products\/9781394306237","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}