Quantum-Inspired Machine Learning for 6G: Fundamentals, Security, Resource Allocations, Challenges, and Future Research Directions-Reference-Cited by-同舟云学术

Quantum-Inspired Machine Learning for 6G: Fundamentals, Security, Resource Allocations, Challenges, and Future Research Directions

Author:

Duong Trung Q.¹^ORCID,Ansere James Adu²,Narottama Bhaskara³^ORCID,Sharma Vishal¹,Dobre Octavia A.⁴^ORCID,Shin Hyundong⁵^ORCID

Affiliation:

1. School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, U.K.

2. Department of Electrical and Electronic Engineering, Sunyani Technical University, Sunyani, Ghana

3. Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea

4. Faculty of Engineering and Applied Science, Memorial University, St. John's, NL, Canada

5. Kyung Hee University, Gyeonggi-do, South Korea

Funder

Engineering and Physical Sciences Research Council

Royal Academy of Engineering

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Automotive Engineering

Link

Reference93 articles.

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