Synopsis
This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks.
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From the Back Cover
This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks.
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Deep Learning in Ad-Hoc Wireless Networks
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks. 132 pp. Englisch. Seller Inventory # 9783031860744
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Deep Learning in Ad-Hoc Wireless Networks (Studies in Big Data, 172)
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Buch. Condition: Neu. Deep Learning in Ad-Hoc Wireless Networks | Gokhan Altan (u. a.) | Buch | Studies in Big Data | v | Englisch | 2025 | Springer | EAN 9783031860744 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 132590553
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 132 pp. Englisch. Seller Inventory # 9783031860744
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents innovative applications of deep learning techniques in wireless ad-hoc networks, addressing critical challenges such as trust, routing, traffic management, and intrusion detection. By combining advanced AI models with real-world network scenarios, the chapters explore novel solutions for improving network reliability, security, and efficiency. Readers benefit from a multidisciplinary approach that bridges deep learning and wireless communication, offering both theoretical insights and practical frameworks. Targeting researchers, engineers, and graduate students, this work serves as a valuable resource for understanding and implementing deep learning strategies to optimize modern wireless systems. Whether improving IoT networks, securing controller area networks, or enabling smart mobility, the book provides actionable knowledge on Deep Learning applications for solving current and future challenges in ad-hoc wireless networks. Seller Inventory # 9783031860744
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