Deep Learning in Ad-Hoc Wireless Networks

Gokhan Altan

ISBN 10: 3031860748 / ISBN 13: 9783031860744

Published by Springer, Palgrave Macmillan Apr 2025, 2025

About this Item

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

Bibliographic Details

• Title: Deep Learning in Ad-Hoc Wireless Networks
• Publisher: Springer, Palgrave Macmillan Apr 2025
• Publication Date: 2025
• Language: English
• ISBN 10: 3031860748
• ISBN 13: 9783031860744
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 13D millimeters 241 millimeters width by 160 millimeters height by 13 millimeters depth
• Weight: 393 grams

About this title

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.