Blind Modulation Classification via Combined Machine Learning and Signal Feature Extraction-Reference-Cited by-同舟云学术

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Blind Modulation Classification via Combined Machine Learning and Signal Feature Extraction

Published:2022-01-29 Issue: Volume: Page:
ISSN:
Container-title:2021 International Seminar on Machine Learning, Optimization, and Data Science (ISMODE)
language:
Short-container-title:

Author:

Norolahi J.¹,Mehrnia M.²,Azmi P.¹

Affiliation:

1. Tarbiat Modares University,dept. Electrical and Computer Engineering,Tehran,Iran

2. Illinois Institute of Technology,dept. Electrical and Computer Engineering,Chicago,United State

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9741823/9741833/09742733.pdf?arnumber=9742733

Reference21 articles.

1. Convolutional Radio Modulation Recognition Networks

2. A Low-Power Processor With Configurable Embedded Machine-Learning Accelerators for High-Order and Adaptive Analysis of Medical-Sensor Signals

3. LIBSVM: a library for support vector machines;chang;ACM transactions on intelligent systems and echnology (TIST),2011

4. Modulation classification method for frequency modulation signals based on the time–frequency distribution and CNN

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A machine learning based algorithm for joint improvement of power control, link adaptation, and capacity in beyond 5G communication systems;Telecommunication Systems;2023-05-22

2. A Machine Learning Based Algorithm for Joint Improvement of Power Control, link adaptation, and Capacity in Beyond 5G Communication systems;2022-08-22

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