SULJE VALIKKO

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Nguyen Van Hoang | Akateeminen Kirjakauppa

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Deep Reinforcement Learning for Wireless Communications and Networking - Theory, Applications and Implementation
Dinh Thai Hoang; Nguyen Van Huynh; Diep N. Nguyen; Ekram Hossain; Dusit Niyato
John Wiley & Sons Inc (2023)
Kovakantinen kirja
126,70
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Tourism and Poverty Alleviation in Nature Conservation Areas - A Comparative Study Between Japan and Vietnam
Nguyen Van Hoang
Taylor & Francis Ltd (2024)
Kovakantinen kirja
62,90
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ostoskoriin kpl
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Ambient Backscatter Communication Networks
Dinh Thai Hoang; Dusit Niyato; Dong In Kim; Nguyen Van Huynh; Shimin Gong
Cambridge University Press (2020)
Kovakantinen kirja
130,40
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Advances in Asian Mechanism and Machine Science : Proceedings of IFToMM Asian MMS 2021
Nguyen Van Khang (ed.); Nguyen Quang Hoang (ed.); Marco Ceccarelli (ed.)
Springer (2021)
Kovakantinen kirja
215,70
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ostoskoriin kpl
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Advances in Asian Mechanism and Machine Science : Proceedings of IFToMM Asian MMS 2021
Nguyen Van Khang (ed.); Nguyen Quang Hoang (ed.); Marco Ceccarelli (ed.)
Springer (2022)
Pehmeäkantinen kirja
215,70
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From Smart City to Smart Factory for Sustainable Future: Conceptual Framework, Scenarios, and  Multidiscipline Perspectives
Marek Pagac; Jiri Hajnys; Tomasz Kozior; Hoang-Sy Nguyen; Van Dung Nguyen; Akash Nag
Springer International Publishing AG (2024)
Pehmeäkantinen kirja
147,10
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ostoskoriin kpl
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Credit Scoring Models for Vietnamese Market
Dao Thi Thanh Binh; Hoang Thi Yen; Nguyen Van Trang
LAP Lambert Academic Publishing (2012)
Pehmeäkantinen kirja
83,40
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Using Alternative Assessment to Improve EFL Learners' Learning Achievement - From Theory to Practice
Hoang Yen Phuong; Thi Van Su Nguyen
Nova Science Publishers Inc (2019)
Pehmeäkantinen kirja
145,40
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Industrial Networks and Intelligent Systems : 7th EAI International Conference, INISCOM 2021, Hanoi, Vietnam, April 22-23, 2021,
Nguyen-Son Vo (ed.); Van-Phuc Hoang (ed.); Quoc-Tuan Vien (ed.)
Springer (2021)
Pehmeäkantinen kirja
49,60
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Industrial Networks and Intelligent Systems : 6th EAI International Conference, INISCOM 2020, Hanoi, Vietnam, August 27–28, 2020
Nguyen-Son Vo (ed.); Van-Phuc Hoang (ed.)
Springer (2020)
Pehmeäkantinen kirja
49,60
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Advances in Information and Communication Technology : Proceedings of the 2nd International Conference ICTA 2023, Volume 1
Phung Trung Nghia (ed.); Vu Duc Thai (ed.); Nguyen Thanh Thuy (ed.); Le Hoang Son (ed.); Van-Nam Huynh (ed.)
Springer (2023)
Pehmeäkantinen kirja
155,60
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Advances in Information and Communication Technology : Proceedings of the 2nd International Conference ICTA 2023, Volume 2
Phung Trung Nghia (ed.); Vu Duc Thai (ed.); Nguyen Thanh Thuy (ed.); Le Hoang Son (ed.); Van-Nam Huynh (ed.)
Springer (2024)
Pehmeäkantinen kirja
172,80
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Deep Reinforcement Learning for Wireless Communications and Networking - Theory, Applications and Implementation
126,70 €
John Wiley & Sons Inc
Sivumäärä: 288 sivua
Asu: Kovakantinen kirja
Julkaisuvuosi: 2023, 25.07.2023 (lisätietoa)
Kieli: Englanti
Deep Reinforcement Learning for Wireless Communications and Networking Comprehensive guide to Deep Reinforcement Learning (DRL) as applied to wireless communication systems

Deep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while providing fundamental knowledge about theories, formulation, design, learning models, algorithms and implementation of DRL together with a particular case study to practice. The book also covers diverse applications of DRL to address various problems in wireless networks, such as caching, offloading, resource sharing, and security. The authors discuss open issues by introducing some advanced DRL approaches to address emerging issues in wireless communications and networking.

Covering new advanced models of DRL, e.g., deep dueling architecture and generative adversarial networks, as well as emerging problems considered in wireless networks, e.g., ambient backscatter communication, intelligent reflecting surfaces and edge intelligence, this is the first comprehensive book studying applications of DRL for wireless networks that presents the state-of-the-art research in architecture, protocol, and application design.

Deep Reinforcement Learning for Wireless Communications and Networking covers specific topics such as:



Deep reinforcement learning models, covering deep learning, deep reinforcement learning, and models of deep reinforcement learning
Physical layer applications covering signal detection, decoding, and beamforming, power and rate control, and physical-layer security
Medium access control (MAC) layer applications, covering resource allocation, channel access, and user/cell association
Network layer applications, covering traffic routing, network classification, and network slicing

With comprehensive coverage of an exciting and noteworthy new technology, Deep Reinforcement Learning for Wireless Communications and Networking is an essential learning resource for researchers and communications engineers, along with developers and entrepreneurs in autonomous systems, who wish to harness this technology in practical applications.

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Tilaustuote | Arvioimme, että tuote lähetetään meiltä noin 4-5 viikossa | Tilaa jouluksi viimeistään 27.11.2024
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Helsinki
Tapiola
Turku
Tampere
Deep Reinforcement Learning for Wireless Communications and Networking - Theory, Applications and Implementationzoom
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ISBN:
9781119873679
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