9781119873679 - deep reinforcement learning for wireless communications and networking: theory, applications and implementation de hoang, dinh thai; huynh, nguyen van; nguyen, diep n.; hossain, ekram; niyato, dusit (19 resultados)
Deep Reinforcement Learning for Wireless Communications and Networking: Theory, Applications and Implementation
Hoang, Dinh Thai; Huynh, Nguyen Van; Nguyen, Diep N.; Hossain, Ekram; Niyato, Dusit
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Deep Reinforcement Learning for Wireless Communications and Networking : Theory, Applications and Implementation
Hoang, Dinh Thai; Van Huynh, Nguyen; Nguyen, Diep N.; Hossain, Ekram; Niyato, Dusit
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Deep Reinforcement Learning for Wireless Communications and Networking: Theory, Applications and Implementation
Hoang, Dinh Thai; Huynh, Nguyen Van; Nguyen, Diep N.; Hossain, Ekram; Niyato, Dusit
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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Deep Reinforcement Learning for Wireless Communications and Networking : Theory, Applications and Implementation
Hoang, Dinh Thai; Van Huynh, Nguyen; Nguyen, Diep N.; Hossain, Ekram; Niyato, Dusit
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Deep Reinforcement Learning for Wireless Communications and Networking : Theory, Applications and Implementation
Hoang, Dinh Thai; Van Huynh, Nguyen; Nguyen, Diep N.; Hossain, Ekram; Niyato, Dusit
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Deep Reinforcement Learning for Wireless Communications and Networking: Theory, Applications and Implementation
Hoang, Dinh Thai; Huynh, Nguyen Van; Nguyen, Diep N.; Hossain, Ekram; Niyato, Dusit
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Deep Reinforcement Learning for Wireless Communications and Networking : Theory, Applications and Implementation
Hoang, Dinh Thai; Van Huynh, Nguyen; Nguyen, Diep N.; Hossain, Ekram; Niyato, Dusit
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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Condición: New. 2023. 1st Edition. Hardcover. . . . . .
Deep Reinforcement Learning for Wireless Communications and Networking: Theory, Applications and Implementation
Hoang, Dinh Thai; Huynh, Nguyen Van; Nguyen, Diep N.; Hossain, Ekram; Niyato, Dusit
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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Librería: moluna, Greven, Alemaniamoluna
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EUR 127,22
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Condición: New. Dinh Thai Hoang, Ph.D., is a faculty member at the University of Technology Sydney, Australia. He is also an Associate Editor of IEEE Communications Surveys & Tutorials and an Editor of IEEE Transactions on Wireless Communications, IEEE Transactions on Cogn.
Deep Reinforcement Learning for Wireless Communica tions and Networking: Theory, Applications and Imp lementation
Hoang, Dinh Thai/ Van Huynh, Nguyen/ Nguyen, Diep N./ Hossain, Ekram/ Niyato, Dusit
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 352 pages. 9.00x6.00x0.69 inches. In Stock.
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Condición: New. 2023. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Buch. Condición: Neu. Neuware - Deep Reinforcement Learning for Wireless Communications and NetworkingComprehensive guide to Deep Reinforcement Learning (DRL) as applied to wireless communication systemsDeep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while pro…viding 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 slicingWith 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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Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
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EUR 136,37
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Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 975.
Deep Reinforcement Learning for Wireless Communica tions and Networking: Theory, Applications and Imp lementation
Hoang, Dinh Thai/ Van Huynh, Nguyen/ Nguyen, Diep N./ Hossain, Ekram/ Niyato, Dusit
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- Impresión bajo demanda
Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 154,45
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Hardcover. Condición: Brand New. 352 pages. 9.00x6.00x0.69 inches. In Stock. This item is printed on demand.
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 124,25
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Hardcover. Condición: new. Hardcover. 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 w…hile 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 learningPhysical layer applications covering signal detection, decoding, and beamforming, power and rate control, and physical-layer securityMedium access control (MAC) layer applications, covering resource allocation, channel access, and user/cell associationNetwork 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
