dc.contributor.editor | Sun, Yichuang | |
dc.contributor.editor | Lee, Haeyoung | |
dc.contributor.editor | Simpson, Oluyomi | |
dc.date.accessioned | 2024-04-22T12:45:02Z | |
dc.date.available | 2024-04-22T12:45:02Z | |
dc.date.issued | 2024-04-18 | |
dc.identifier.citation | Sun , Y , Lee , H & Simpson , O (eds) 2024 , Machine Learning in Communication Systems and Networks . MDPI Multidisciplinary Digital Publishing Institute . https://doi.org/10.3390/books978-3-7258-0726-0 | |
dc.identifier.isbn | 978-3-7258-0725-3 | |
dc.identifier.isbn | 978-3-7258-0726-0 | |
dc.identifier.other | ORCID: /0000-0002-5760-6623/work/158538221 | |
dc.identifier.uri | http://hdl.handle.net/2299/27784 | |
dc.description | © 2024 The Author(s). Articles in this book are Open Access and distributed under the Creative CommonsAttribution (CC BY) license. The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) license, https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.description.abstract | Recent advances in machine learning, coupled with the availability of powerful computing platforms, have garnered significant attention from academic, research, and industry communities. Machine learning is considered a promising tool to tackle the challenge posed by increasingly complex, heterogeneous, and dynamic communication environments. It holds the potential to contribute to the intelligent management and optimization of communication systems and networks by enabling us to predict changes, find patterns of uncertainties in the communication environment, and make data-driven decisions. This Topic seeks to explore the intersection of machine learning and communication research, showcasing a compilation of cutting-edge contributions which underscore the transformative potential of machine learning as a driving force behind adaptive and intelligent communication. | en |
dc.format.extent | 398 | |
dc.format.extent | 41356603 | |
dc.language.iso | eng | |
dc.publisher | MDPI Multidisciplinary Digital Publishing Institute | |
dc.subject | wireless communications | |
dc.subject | Mobile communications | |
dc.subject | Vehicular communication | |
dc.subject | 5G/6G systems and networks | |
dc.subject | Artificial intelligence | |
dc.subject | Machine learning | |
dc.subject | Deep Learning | |
dc.title | Machine Learning in Communication Systems and Networks | en |
dc.contributor.institution | Centre for Future Societies Research | |
dc.contributor.institution | School of Physics, Engineering & Computer Science | |
dc.contributor.institution | Department of Engineering and Technology | |
dc.contributor.institution | Communications and Intelligent Systems | |
dc.contributor.institution | Centre for Engineering Research | |
dc.identifier.url | https://www.mdpi.com/books/reprint/9138-machine-learning-in-communication-systems-and-networks | |
rioxxterms.versionofrecord | 10.3390/books978-3-7258-0726-0 | |
rioxxterms.type | Book | |
herts.preservation.rarelyaccessed | true | |