Cantitate/Preț
Produs

Mobile Edge Artificial Intelligence: Opportunities and Challenges

Autor Yuanming Shi, Kai Yang, Zhanpeng Yang, Yong Zhou
en Limba Engleză Paperback – 17 aug 2021
Mobile Edge Artificial Intelligence: Opportunities and Challenges presents recent advances in wireless technologies and nonconvex optimization techniques for designing efficient edge AI systems. The book includes comprehensive coverage on modeling, algorithm design and theoretical analysis. Through typical examples, the powerfulness of this set of systems and algorithms is demonstrated, along with their abilities to make low-latency, reliable and private intelligent decisions at network edge. With the availability of massive datasets, high performance computing platforms, sophisticated algorithms and software toolkits, AI has achieved remarkable success in many application domains.
As such, intelligent wireless networks will be designed to leverage advanced wireless communications and mobile computing technologies to support AI-enabled applications at various edge mobile devices with limited communication, computation, hardware and energy resources.


  • Presents advanced key enabling techniques, including model compression, wireless MapReduce and wireless cooperative transmission
  • Provides advanced 6G wireless techniques, including over-the-air computation and reconfigurable intelligent surface
  • Includes principles for designing communication-efficient edge inference systems, communication-efficient training systems, and communication-efficient optimization algorithms for edge machine learning
Citește tot Restrânge

Preț: 55316 lei

Preț vechi: 101715 lei
-46% Nou

Puncte Express: 830

Preț estimativ în valută:
10587 11011$ 8872£

Carte tipărită la comandă

Livrare economică 06-20 martie

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9780128238172
ISBN-10: 0128238178
Pagini: 206
Dimensiuni: 152 x 229 mm
Greutate: 0.28 kg
Editura: ELSEVIER SCIENCE

Public țintă

Scientists and researchers, postgraduates, undergraduates, practitioners and professionals in electronic engineering and computer science

Cuprins

I. Introduction and Overview
1. Primer on Artificial Intelligence
2. Overview of Edge AI Systems
II. Edge Inference
3. Model Compression for On-Device Inference
4. Wireless MapReduce for Device Distributed Inference
5. Wireless Cooperative Transmission for Edge Inference
III. Edge Training
6. Over-the-Air Computation for Federated Learning
7. Blind Over-the-Air Computation for Federated Learning
8. Reconfigurable Intelligent Surface Aided Federated Learning System
IV. Future Directions
9. Communication-Efficient Algorithms for Edge AI
10. Future Research Directions