Deep Quantum Neural Networks : AI for 6G/7G Communication Systems / / edited by Abhishek Kumar, Pramod Singh Rathore, Reyes Juárez-Ramírez

• Autore: Kumar Abhishek
• Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026
• Edizione: 1st ed. 2026.
• Descrizione fisica: 1 online resource (285 pages)
• Disciplina: 530.12; 652.8
• Soggetto topico: Quantum communication; Neural networks (Computer science); Wireless communication systems; Mobile communication systems; Artificial intelligence; Quantum Communications and Cryptography; Mathematical Models of Cognitive Processes and Neural Networks; Wireless and Mobile Communication; Artificial Intelligence
• Altri autori: RathorePramod Singh Juárez-RamírezReyes
• Nota di contenuto: Quantum Neural Networks in 6G/7G Communication Systems.-Tensor Networks in Quantum Neural Network Architectures -- n-Sci: Bridging Science and Quantum Neural Networks -- Quantum-Assisted Channel Estimation for 6G/7G Networks -- n-Sci and Tensor Networks in Smart City and IoT Deployments -- Quantum Neural Networks in Satellite and Space-Based 7G Communications -- Enhancing URLLC in 6G/7G Using Quantum Neural Networks -- Energy-Efficient 7G Networks Using Tensor and Quantum Neural Networks -- Quantum Neural Networks for Security in 6G/7G -- New Paradigms in Edge Computing with Quantum Neural Networks -- Towards Standardization: Quantum Neural Networks in Global 7G Standards -- Quantum Neural Networks for Autonomous 7G Vehicle Communication -- Quantum Neural Networks in Healthcare and Critical Systems -- Tensor Networks and n-Sci: The Road to Beyond 7G -- Quantum Neural Networks in Post-7G Communication.
• Sommario/riassunto: This book looks at how quantum computing, neural networks, and next-generation communication systems can work together in new and exciting ways. The book presents details about cutting edge techniques, such as Tensor Networks and the n-Sci framework, that make 6G and 7G networks faster, safer, and able to grow. It has in-depth discussion on quantum-assisted channel estimates, energy-efficient designs, and ultra-reliable low-latency communication (URLLC), which makes it an important tool for wireless communication scholars and engineers. Some of the unique features are- in-depth case studies, real-life examples in smart cities and autonomous systems, and the use of graphs and tables to make complicated ideas easy to understand. Readers will learn a lot about how future communication will work and how quantum neural networks can be used to change the development of global wireless standards.
• Titolo autorizzato: Deep Quantum Neural Networks
• ISBN: 981-9516-83-8
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911049073803321
• Lo trovi qui: Univ. Federico II
• Serie: Signals and Communication Technology, . 1860-4870