Generative Adversarial Network-Based Signal Inpainting for Automatic Modulation Classification-Reference-Cited by-同舟云学术

Generative Adversarial Network-Based Signal Inpainting for Automatic Modulation Classification

Author:

Lee Subin¹^ORCID,Yoon Young-Il²,Jung Yong Ju¹^ORCID

Affiliation:

1. School of Computing, Gachon University, Seongnam, Republic of Korea

2. Research and Development Center, LIG Nex1, Seongnam, Republic of Korea

Funder

Korea Research Institute for Defense Technology Planning and Advancement

Defence Acquisition Program Administration

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference57 articles.

1. Radio machine learning dataset generation with GNU radio;o’shea;Proc GNU Radio Conf,2016

2. Adam: A method for stochastic optimization;kingma;arXiv 1412 6980,2014

3. Gnu radio: Tools for exploring the radio frequency spectrum;blossom;Linux J,2004

4. PyTorch: An imperative style, high-performance deep learning library;paszke;Proc Adv Neural Inf Process Syst,2019

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