Machine Learning for Wireless Communication (eBook, PDF)
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Machine Learning for Wireless Communication (eBook, PDF)
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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.…mehr
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- Produktdetails
- Verlag: Springer Nature Switzerland
- Seitenzahl: 119
- Erscheinungstermin: 12. August 2025
- Englisch
- ISBN-13: 9783031941177
- Artikelnr.: 75180109
- Verlag: Springer Nature Switzerland
- Seitenzahl: 119
- Erscheinungstermin: 12. August 2025
- Englisch
- ISBN-13: 9783031941177
- Artikelnr.: 75180109
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
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.







