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Deep Learning Approaches in Intelligent Wireless Networking
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Deep Learning Approaches in Intelligent Wireless Networking
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Deep Learning-Based Approaches for Sentiment Analysis (Algorithms for Intelligent Systems)
Book 11 of 95: Algorithms for Intelligent SystemsSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Deep Learning-Based Approaches for Sentiment Analysis (Algorithms for Intelligent Systems)
Book 11 of 95: Algorithms for Intelligent SystemsSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Deep Learning Approaches in Intelligent Wireless Networking
Language: English
Published by Taylor & Francis Ltd, 2026
ISBN 10: 1032998156 ISBN 13: 9781032998152
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Add to basketCondition: New. Bharat Bhushan is an Associate Professor at Department of Computer Science and Engineering, Sharda School of Computing Science & Engineering, Sharda University, Greater Noida, India.Mohd Anas Wajid is an Assistant Professor and P.
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Add to basketHardcover. Condition: Brand New. 336 pages. 9.18x6.12x9.45 inches. In Stock.
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Deep Learning Approaches in Intelligent Wireless Networking
Language: English
Published by Taylor & Francis Ltd Apr 2026, 2026
ISBN 10: 1032998156 ISBN 13: 9781032998152
Buch. Condition: Neu. Neuware - This reference text covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and elaborates discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. It further presents concepts and theories related to high-speed communication systems which are important in intelligent wireless communications.
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Deep Learning Approaches in Intelligent Wireless Networking (Hardcover)
Language: English
Published by Taylor & Francis Ltd, London, 2026
ISBN 10: 1032998156 ISBN 13: 9781032998152
Hardcover. Condition: new. Hardcover. This reference text covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and engages in a discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. It further presents concepts and theories related to high-speed communication systems, which are important in intelligent wireless communications.Features: Discusses machine learning-based network management strategy in wireless systems, and machine learning-inspired big data analytics frameworks for wireless network applications. Presents high-speed communication systems, deep learning for wireless networks, security aspects in wireless networks, and decision-making for wireless networks. Highlights the importance of using deep reinforcement learning in intelligent wireless networks and deep reinforcement learning-based mobile data offloading frameworks. Covers novel network architectures for distributed edge learning, and privacy issues in distributed edge learning. Illustrates experimentation and deep learning-based simulations in networking systems, deep learning-based communication frameworks for multiuser detection and sparse channel estimation.The book is written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. This book covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and elaborates discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Deep Learning Approaches in Intelligent Wireless Networking
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Add to basketHRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Deep Learning Approaches in Intelligent Wireless Networking (Hardcover)
Language: English
Published by Taylor & Francis Ltd, London, 2026
ISBN 10: 1032998156 ISBN 13: 9781032998152
US$ 177.98
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Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: new. Hardcover. This reference text covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and engages in a discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. It further presents concepts and theories related to high-speed communication systems, which are important in intelligent wireless communications.Features: Discusses machine learning-based network management strategy in wireless systems, and machine learning-inspired big data analytics frameworks for wireless network applications. Presents high-speed communication systems, deep learning for wireless networks, security aspects in wireless networks, and decision-making for wireless networks. Highlights the importance of using deep reinforcement learning in intelligent wireless networks and deep reinforcement learning-based mobile data offloading frameworks. Covers novel network architectures for distributed edge learning, and privacy issues in distributed edge learning. Illustrates experimentation and deep learning-based simulations in networking systems, deep learning-based communication frameworks for multiuser detection and sparse channel estimation.The book is written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. This book covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and elaborates discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Deep Learning-Based Approaches for Sentiment Analysis (Algorithms for Intelligent Systems)
Book 11 of 95: Algorithms for Intelligent SystemsUS$ 228.81
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Ships from United Kingdom to U.S.A.Quantity: 4 available
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Deep Learning-Based Approaches for Sentiment Analysis (Algorithms for Intelligent Systems)
Book 11 of 95: Algorithms for Intelligent SystemsUS$ 243.72
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Ships from United Kingdom to U.S.A.Quantity: 4 available
Add to basketCondition: New. Print on Demand.
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Deep Learning Approaches in Intelligent Wireless Networking (Hardcover)
Language: English
Published by Taylor & Francis Ltd, London, 2026
ISBN 10: 1032998156 ISBN 13: 9781032998152
Hardcover. Condition: new. Hardcover. This reference text covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and engages in a discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. It further presents concepts and theories related to high-speed communication systems, which are important in intelligent wireless communications.Features: Discusses machine learning-based network management strategy in wireless systems, and machine learning-inspired big data analytics frameworks for wireless network applications. Presents high-speed communication systems, deep learning for wireless networks, security aspects in wireless networks, and decision-making for wireless networks. Highlights the importance of using deep reinforcement learning in intelligent wireless networks and deep reinforcement learning-based mobile data offloading frameworks. Covers novel network architectures for distributed edge learning, and privacy issues in distributed edge learning. Illustrates experimentation and deep learning-based simulations in networking systems, deep learning-based communication frameworks for multiuser detection and sparse channel estimation.The book is written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. This book covers deep learning-based communication frameworks for multiuser detection and sparse channel estimation and elaborates discussion on deep learning-based ultra-dense cell communication and sensor networks and ad-hoc communication. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
