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  4. Neural Networks & Machine Learning in Cognitive Radar
 
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2020
Conference Paper
Title

Neural Networks & Machine Learning in Cognitive Radar

Abstract
This paper reports on how neural networks and machine learning can support the development of cognitive radar systems. We discuss the aspects of cognition that can be supported by neural networks, review the recent literature on the use of neural networks for radar and review the significant challenges to implementation. The paper concludes with an example where a neural network, trained using reinforcement learning, generates radar waveforms containing a 26 dB notch in the power spectral density. The notch location is specified using a spectral mask that is the input to the neural network.
Author(s)
Smith, Graeme E.
Gurbuz, Sevgi Z.
Brüggenwirth, Stefan  
John-Baptiste, Peter
Mainwork
IEEE Radar Conference, RadarConf 2020  
Conference
Radar Conference (RadarConf) 2020  
DOI
10.1109/RadarConf2043947.2020.9266670
Language
English
Fraunhofer-Institut für Hochfrequenzphysik und Radartechnik FHR  
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