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Deep Learning for RF Signal Classification in Unknown and Dynamic
  Spectrum Environments

Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments

25 September 2019
Yi Shi
Kemal Davaslioglu
Y. Sagduyu
William C. Headley
Michael Fowler
Gilbert Green
ArXivPDFHTML

Papers citing "Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments"

14 / 14 papers shown
Title
IoT Network Security from the Perspective of Adversarial Deep Learning
IoT Network Security from the Perspective of Adversarial Deep Learning
Y. Sagduyu
Yi Shi
T. Erpek
AAML
40
78
0
31 May 2019
Generative Adversarial Network for Wireless Signal Spoofing
Generative Adversarial Network for Wireless Signal Spoofing
Yi Shi
Kemal Davaslioglu
Y. Sagduyu
GAN
AAML
39
78
0
03 May 2019
Spectrum Data Poisoning with Adversarial Deep Learning
Spectrum Data Poisoning with Adversarial Deep Learning
Yi Shi
T. Erpek
Y. Sagduyu
Jason H. Li
AAML
40
72
0
26 Jan 2019
The Importance of Being Earnest: Performance of Modulation
  Classification for Real RF Signals
The Importance of Being Earnest: Performance of Modulation Classification for Real RF Signals
Colin de Vrieze
L. Simić
P. Mähönen
34
17
0
17 Sep 2018
Deep Learning for Launching and Mitigating Wireless Jamming Attacks
Deep Learning for Launching and Mitigating Wireless Jamming Attacks
T. Erpek
Y. Sagduyu
Yi Shi
AAML
43
192
0
03 Jul 2018
Generative Adversarial Learning for Spectrum Sensing
Generative Adversarial Learning for Spectrum Sensing
Kemal Davaslioglu
Y. Sagduyu
GAN
41
89
0
02 Apr 2018
Over the Air Deep Learning Based Radio Signal Classification
Over the Air Deep Learning Based Radio Signal Classification
Tim O'Shea
Tamoghna Roy
T. Clancy
71
1,081
0
13 Dec 2017
Artificial Neural Networks-Based Machine Learning for Wireless Networks:
  A Tutorial
Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial
Mingzhe Chen
Ursula Challita
Walid Saad
Changchuan Yin
Mérouane Debbah
60
208
0
09 Oct 2017
Overcoming catastrophic forgetting in neural networks
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick
Razvan Pascanu
Neil C. Rabinowitz
J. Veness
Guillaume Desjardins
...
A. Grabska-Barwinska
Demis Hassabis
Claudia Clopath
D. Kumaran
R. Hadsell
CLL
352
7,498
0
02 Dec 2016
TensorFlow: A system for large-scale machine learning
TensorFlow: A system for large-scale machine learning
Martín Abadi
P. Barham
Jianmin Chen
Zhiwen Chen
Andy Davis
...
Vijay Vasudevan
Pete Warden
Martin Wicke
Yuan Yu
Xiaoqiang Zhang
GNN
AI4CE
429
18,346
0
27 May 2016
Convolutional Radio Modulation Recognition Networks
Convolutional Radio Modulation Recognition Networks
Tim O'Shea
Johnathan Corgan
T. Clancy
33
1,086
0
12 Feb 2016
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.7K
150,006
0
22 Dec 2014
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies,
  and Applications
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Mohammad Abu Alsheikh
Shaowei Lin
Dusit Niyato
H. Tan
58
827
0
18 May 2014
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based
  Neural Networks
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
Ian Goodfellow
M. Berk Mirza
Xia Da
Aaron Courville
Yoshua Bengio
144
1,442
0
21 Dec 2013
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