商品描述
This book covers the basic principles of wireless communication while delving into the fundamentals of machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning. The authors provide real-world examples and case studies to illustrate the use of machine learning in wireless communication applications such as channel estimation, mobility prediction, resource allocation, and beamforming. This book is an essential resource for researchers, engineers, and students interested in understanding and applying machine learning techniques in the context of wireless communication systems.
商品描述(中文翻譯)
本書涵蓋無線通信的基本原則，同時深入探討機器學習的基本概念，包括監督式學習、非監督式學習、深度學習和強化學習。作者提供了實際案例和案例研究，以說明機器學習在無線通信應用中的使用，例如通道估計、移動預測、資源分配和波束成形。本書是研究人員、工程師和學生了解並應用機器學習技術於無線通信系統中的重要資源。
作者簡介
Dr. Rohit Thanki is a seasoned AI researcher and data scientist with over 12 years of scientific research experience and over 5 years in AI-powered MedTech startups. He held leadership roles such as Head of R&D at Prognica Labs, Dubai, and worked as a Software Consultant at Ennoventure Technologies, India. He earned his Ph.D. in biometric security and data encryption from C. U. Shah University, Gujarat, India. He has since mentored several Ph.D. and master's research students across institutions in Germany and India. His expertise spans medical image analysis, artificial intelligence, machine learning, computer vision, digital watermarking, content security, and signal processing. He has led AI projects involving a variety of medical imaging modalities, including X-ray, MRI, CT, ultrasound, and mammography. Stanford University and Elsevier recognized Dr. Thanki among the Top 2% of AI and image processing scientists in 2024. He has authored over 20 technical books (16 of which are indexed in Scopus) and published more than 100 research articles in reputed journals and conferences indexed in Scopus and the Web of Science. His work has been cited over 2,400 times and has an h-index of 23. Dr. Thanki is an active Senior Member of IEEE and the German AI Association. He serves on editorial boards for several international journals, including BMC Digital Health (Springer Nature) and PLOS ONE. He is also a frequent reviewer for top-tier journals such as IEEE Access, Pattern Recognition, and the IEEE Journal of Biomedical and Health Informatics. His current research focuses on integrating AI in medical diagnostics, explaining AI in healthcare, and using cryptographic techniques for medical data security. He is passionate about bridging clinical practice with cutting-edge AI technology to enhance diagnostic accuracy and patient outcomes. Dr. Komal Borisagar is working as a associate professor at Gujarat Technological University (State University) in the department named Graduate School of Engineering and Technology, Ahmedabad. She has obtained her Ph.D. in Speech Enhancement Techniques for Digital Hearing Aids. Her areas of interest are wireless communication, sensor networks, signal processing, signals & systems and Internet of Things. She has teaching experience of over 20 years. She has published 5 books, 4 book chapters and more than 70 research papers to her credit in referred & indexed journals, conferences at international and in IEEE digital library. She has achieved best paper award five times for her research articles and presentation. She is awarded with "Best Women Engineer Award" in 2019 by Indian Society of Technical Education, Gujarat. She is handling project and research in the filed of IoT and Wireless Communication. Dr. Anjali Diwan is a highly experienced academic and software industry professionalwith over 20 years of expertise. Her areas of academic and research interests include Machine Learning, Image Processing, Artificial Intelligence, Deep Learning, Data Security, Multimedia Forensics, and the application of technologies to address humanitarian challenges. She is a senior member of IEEE and currently serves as a member of the SAC team of IEEE R10 (2023-2024) and the Section Chair of the IEEE Young Professionals affinity group of Gujarat section (2022-2024). Previously, she served as the Section Chair of Student Activity for IEEE Gujarat from 2016 to 2019 and IEEE WIE affinity group co-chair of IEEE Gujarat section from 2014 to 2017. Additionally, Dr. Diwan is a member of the TPC committee of several IEEE conferences and serves as a reviewer for international journals and IEEE transection. Currently she is working as faculty member of CE-AI/Big data department of Marwadi University, Rajkot (Gujarat) in India.
作者簡介(中文翻譯)
羅希特·坦基博士是一位經驗豐富的人工智慧研究員和數據科學家，擁有超過12年的科學研究經驗以及超過5年的人工智慧驅動的醫療科技初創公司經歷。他曾擔任杜拜Prognica Labs的研發部門負責人，並在印度Ennoventure Technologies擔任軟體顧問。他在印度古吉拉特邦的C. U. Shah University獲得生物識別安全和數據加密的博士學位。此後，他指導了多位來自德國和印度的博士及碩士研究生。他的專業領域包括醫學影像分析、人工智慧、機器學習、計算機視覺、數位水印、內容安全和信號處理。他曾主導多個涉及各種醫學影像模式的人工智慧項目，包括X光、MRI、CT、超聲波和乳腺攝影。斯坦福大學和Elsevier在2024年將坦基博士列為人工智慧和影像處理科學家的前2%。他已出版超過20本技術書籍（其中16本在Scopus中被索引），並在多個知名期刊和會議上發表了超過100篇研究文章，這些期刊和會議均在Scopus和Web of Science中被索引。他的工作被引用超過2400次，h指數為23。坦基博士是IEEE的活躍高級會員及德國人工智慧協會的成員。他擔任多個國際期刊的編輯委員會成員，包括BMC Digital Health（Springer Nature）和PLOS ONE。他也是IEEE Access、Pattern Recognition和IEEE生物醫學與健康資訊期刊等頂級期刊的常任審稿人。他目前的研究重點是將人工智慧整合到醫療診斷中，解釋人工智慧在醫療保健中的應用，以及使用加密技術保障醫療數據安全。他熱衷於將臨床實踐與尖端的人工智慧技術相結合，以提高診斷準確性和病人結果。
科馬爾·博里薩加博士目前在古吉拉特科技大學（州立大學）擔任副教授，任教於位於艾哈邁達巴德的工程與技術研究所。她獲得了數位助聽器的語音增強技術博士學位。她的研究興趣包括無線通信、傳感器網絡、信號處理、信號與系統以及物聯網。她擁有超過20年的教學經驗。她已出版5本書籍、4章書籍以及在國際期刊和IEEE數位圖書館中發表了超過70篇的研究論文。她的研究文章和報告曾五次獲得最佳論文獎。2019年，她獲得了古吉拉特邦印度技術教育協會頒發的「最佳女性工程師獎」。她目前負責物聯網和無線通信領域的項目和研究。
安賈莉·迪萬博士是一位經驗豐富的學術界和軟體產業專業人士，擁有超過20年的專業知識。她的學術和研究興趣包括機器學習、影像處理、人工智慧、深度學習、數據安全、多媒體取證以及應用技術解決人道主義挑戰。她是IEEE的高級會員，目前擔任IEEE R10（2023-2024）的SAC團隊成員，以及古吉拉特分會IEEE青年專業人士親和小組的分會主席（2022-2024）。她曾於2016年至2019年擔任IEEE古吉拉特分會的學生活動分會主席，並於2014年至2017年擔任IEEE古吉拉特分會的IEEE WIE親和小組共同主席。此外，迪萬博士還是多個IEEE會議的TPC委員會成員，並擔任國際期刊和IEEE交易的審稿人。目前，她在印度古吉拉特邦的Marwadi University的CE-AI/大數據系擔任教職。
