JaX: Detecting and Cancelling High-power Jammers Using Convolutional Neural Network

Author:

Nguyen Hai N.1ORCID,Noubir Guevara1ORCID

Affiliation:

1. Northeastern University, Boston, MA, USA

Funder

National Science Foundation

Department of Defense

Office of Naval Research

Publisher

ACM

Reference50 articles.

1. Convolutional Neural Networks for Speech Recognition

2. A jamming-resistant MAC protocol for single-hop wireless networks

3. Christopher M. Bishop . 2006. Pattern Recognition and Machine Learning (Information Science and Statistics) . Springer-Verlag , Berlin, Heidelberg . Christopher M. Bishop. 2006. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag, Berlin, Heidelberg.

4. Jerry T Chiang and Yih-Chun Hu. 2010. Cross-layer jamming detection and mitigation in wireless broadcast networks . IEEE/ACM Transactions on networking , Vol. 19 , 1 ( 2010 ), 286--298. Jerry T Chiang and Yih-Chun Hu. 2010. Cross-layer jamming detection and mitigation in wireless broadcast networks. IEEE/ACM Transactions on networking , Vol. 19, 1 (2010), 286--298.

5. CISCO Meraki. 2018. SNR and Wireless Signal Strength. https://documentation.meraki.com/MR/WiFi_Basics_and_Best_Practices/Signal-to-Noise_Ratio_(SNR)_and_Wireless_Signal_Strength. CISCO Meraki. 2018. SNR and Wireless Signal Strength. https://documentation.meraki.com/MR/WiFi_Basics_and_Best_Practices/Signal-to-Noise_Ratio_(SNR)_and_Wireless_Signal_Strength.

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