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▼a Applications of machine learning in wireless communications /:
▼c edited by Ruisi He and Zhiguo Ding.
▼a London, United Kingdom:
▼b The Institution of Engineering and Technology,
▼c 2019.
▼a 1 online resource (xvi, 474 pages).
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▼a IET Telecommunications series;
▼v 81
▼a Includes bibliographical references and index.
▼a In such an era of big data where data mining and data analysis technologies are effective approaches for wireless system evaluation and design, the applications of machine learning in wireless communications have received a lot of attention recently. Machine learning provides feasible and new solutions for the complex wireless communication system design. It has been a powerful tool and popular research topic with many potential applications to enhance wireless communications, e.g. radio channel modelling, channel estimation and signal detection, network management and performance improvement, access control, resource allocation. However, most of the current researches are separated into different fields and have not been well organized and presented yet. It is therefore difficult for academic and industrial groups to see the potentialities of using machine learning in wireless communications. It is now appropriate to present a detailed guidance of how to combine the disciplines of wireless communications and machine learning.
▼a Online resource; title from PDF title page (IET, viewed September 19, 2019).
▼a Master record variable field(s) change: 650
▼a Wireless communication systems.
▼a Data mining.
▼a Electronic data processing.
▼a Machine learning.
▼a Radio.
▼a Telecommunication
▼x Data processing.
▼a Data mining.
▼2 fast
▼0 (OCoLC)fst00887946
▼a Machine learning.
▼2 fast
▼0 (OCoLC)fst01004795
▼a Radio.
▼2 fast
▼0 (OCoLC)fst01087053
▼a Telecommunication
▼x Data processing.
▼2 fast
▼0 (OCoLC)fst01145844
▼a Wireless communication systems.
▼2 fast
▼0 (OCoLC)fst01176209
▼a Big Data.
▼2 inspect
▼a data analysis.
▼2 inspect
▼a data mining.
▼2 inspect
▼a learning (artificial intelligence).
▼2 inspect
▼a radiocommunication.
▼2 inspect
▼a telecommunication computing.
▼2 inspect
▼a Electronic books.
▼a Electronic books.
▼a He, Ruisi,
▼e editor.
▼a Zhiguo Ding,
▼e editor.
▼i Print version:
▼t Applications of machine learning in wireless communications.
▼d London, United Kingdom : The Institution of Engineering and Technology, 2019,
▼z 1785616579
▼w (OCoLC)1084807888
▼a IET telecommunications series;
▼v 81.
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| 자료유형 : | eBook |
|---|---|
| ISBN : | 9781785616587 |
| ISBN : | 1785616587 |
| ISBN : | |
| ISBN : | |
| 서명/저자사항 : | Applications of machine learning in wireless communications /: edited by Ruisi He and Zhiguo Ding. |
| 발행사항 : | London, United Kingdom: The Institution of Engineering and Technology, 2019. |
| 형태사항 : | 1 online resource (xvi, 474 pages). |
| 총서사항 : | IET Telecommunications series; 81 |
| 서지주기 : | Includes bibliographical references and index. |
| 요약 : | In such an era of big data where data mining and data analysis technologies are effective approaches for wireless system evaluation and design, the applications of machine learning in wireless communications have received a lot of attention recently. Machine learning provides feasible and new solutions for the complex wireless communication system design. It has been a powerful tool and popular research topic with many potential applications to enhance wireless communications, e.g. radio channel modelling, channel estimation and signal detection, network management and performance improvement, access control, resource allocation. However, most of the current researches are separated into different fields and have not been well organized and presented yet. It is therefore difficult for academic and industrial groups to see the potentialities of using machine learning in wireless communications. It is now appropriate to present a detailed guidance of how to combine the disciplines of wireless communications and machine learning. |
| 일반주제명 : | Wireless communication systems. -- |
| 일반주제명 : | Data mining. -- |
| 일반주제명 : | Electronic data processing. -- |
| 일반주제명 : | Machine learning. -- |
| 일반주제명 : | Radio. -- |
| 일반주제명 : | Telecommunication -- Data processing. -- |
| 일반주제명 : | Data mining. -- |
| 일반주제명 : | Machine learning. -- |
| 일반주제명 : | Radio. -- |
| 일반주제명 : | Telecommunication -- Data processing. -- |
| 일반주제명 : | Wireless communication systems. -- |
| 일반주제명 : | Big Data. -- |
| 일반주제명 : | data analysis. -- |
| 일반주제명 : | data mining. -- |
| 일반주제명 : | learning (artificial intelligence). -- |
| 일반주제명 : | radiocommunication. -- |
| 일반주제명 : | telecommunication computing. -- |
| 개인저자 : | He, Ruisi, editor. |
| 개인저자 : | Zhiguo Ding, editor. |
| 기타형태 저록 : | Print version: Applications of machine learning in wireless communications. London, United Kingdom : The Institution of Engineering and Technology, 2019, 1785616579 |
| 언어 | 영어 |
| URL : |
|---|
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