Deep Neural Network Design for Radar Applications /

The book has 11 chapters including a Prologue: perspectives on deep learning of RF data and an Epilogue: looking toward the future; and is divided into 3 parts. The first part deals with Fundamentals and covers the following topics: Radar systems, signals, and phenomenology; Basic principles of mach...

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Bibliographic Details
Other Authors:	Gurbuz, Sevgi Zubeyde (ed.)
Format:	eBook
Language:	English
Published:	Stevenage : SciTech Publishing Incorporated, 2020.
Series:	Radar, Sonar & Navigation.
Subjects:	Detectors. Doppler radar. Imaging. Machine learning. Radar. Signal processing > Digital techniques > Data processing. Synthetic aperture radar. Target acquisition. classification. convolutional neural nets. data structures. learning (artificial intelligence). passive radar. radar applications. radar computing. radar imaging. radar target recognition. remote sensing by radar. sensor fusion. synthetic aperture radar. deep neural network design radar applications deep learning RF data radar systems radar signals radar phenomenology machine learning theoretical foundations radar data representation daily living activities classification DNN training radar microDoppler signatures classification SAR data augmentation deep convolutional neural networks SAR-based automatic target recognition ISAR-based automatic target recognition passive synthetic aperture radar imaging deep representations fusion multistatic radar networks radar remote sensing Electronic books.
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