Few-shot modulation recognition using Recurrence Plot Algorithm
- Title
- Few-shot modulation recognition using Recurrence Plot Algorithm
- Author
- 남해운
- Keywords
- Bioengineering; Communication, Networking and Broadcast Technologies; Components, Circuits, Devices and Systems; Computing and Processing; Fields, Waves and Electromagnetics; Power, Energy and Industry Applications; Signal Processing and Analysis; Transportation; Deep learning; RF signals; Modulation; Imaging; Time-varying channels; Data models; Classification algorithms; Few-shot learning; modulation recognition; Relation Network; Recurrence Plot
- Issue Date
- 2021-10
- Publisher
- 통신학회
- Citation
- 2021 International Conference on Information and Communication Technology Convergence (ICTC) Information and Communication Technology Convergence (ICTC), 2021 International Conference on. :1175-1177 Oct, 2021
- Abstract
- Deep learning techniques have shown high performance for Automatic Modulation Classification (AMC) tasks. However, the tasks need a burden of collecting large-scale annotated data, where the trained network model should be re-trained if new classes are given. In this paper, Few-shot learning (FSL) based AMC is introduced to handle this problem. Also imaging algorithm using recurrence plot (RP) is considered to make the input data more suitable for few shot learning. The results demonstrate that the proposed approach is able to classify images of new classes with high accuracy without further updating the network.
- URI
- https://ieeexplore.ieee.org/document/9620817?arnumber=9620817&SID=EBSCO:edseeehttps://repository.hanyang.ac.kr/handle/20.500.11754/170154
- ISBN
- 978-1-6654-2383-0
- ISSN
- 2162-1233
- DOI
- 10.1109/ICTC52510.2021.9620817
- Appears in Collections:
- COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ELECTRICAL ENGINEERING(전자공학부) > Articles
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