Semi-Supervised Techniques for Detecting Previously Unseen Radar Behaviors
Author:
Affiliation:
1. Department of Electrical and Computer Engineering, Miami University, Oxford, OH, USA
Funder
National Science Foundation’s Industry-University Cooperative Research Centers (IUCRC) Center for Surveillance Research
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
https://ieeexplore.ieee.org/ielam/6287639/10005208/10177924-aam.pdf
Reference21 articles.
1. Recognition of Unknown Radar Emitters With Machine Learning
2. Work modes recognition and boundary identification of MFR pulse sequences with a hierarchical seq2seq LSTM
3. Outlier Analysis
4. A systematic review on intrusion detection based on the Hidden Markov Model
5. Modelling, Learning and Prediction of Complex Radar Emitter Behaviour
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