A Novel Sensing Strategy through Denoising Autoencoder and Ensembling Methods-Reference-Cited by-同舟云学术

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A Novel Sensing Strategy through Denoising Autoencoder and Ensembling Methods

Published:2022-10-19 Issue: Volume: Page:
ISSN:
Container-title:2022 13th International Conference on Information and Communication Technology Convergence (ICTC)
language:
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Author:

Gul Noor¹,Ahmed Saeed²,Kim Su Min³,Kim Junsu³

Affiliation:

1. University of Peshawar,Department of Electronics,Peshawar,Pakistan

2. Mirpur University of Science and Technology,Department of Electrical Engineering,AJK,Pakistan

3. Tech University of Korea,Department of Electronics Engineering,Gyeonggi-do,Korea

Funder

National Research Foundation of Korea

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9952188/9952355/09952715.pdf?arnumber=9952715

Reference13 articles.

1. A Survey on Machine-Learning Techniques in Cognitive Radios

2. Reinforcement learning based sensing policy optimization for energy efficient cognitive radio networks;oksanen;Neurocomputing,2011

3. Machine Learning to Data Fusion Approach for Cooperative Spectrum Sensing

4. Machine Learning Techniques for Cooperative Spectrum Sensing in Cognitive Radio Networks

5. Distributed Gradient Descent Algorithm Robust to an Arbitrary Number of Byzantine Attackers

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