1 option
Deep Neural Network Design for Radar Applications / Sevgi Zubeyde Gurbuz [Ed].
- Format:
- Book
- Series:
- Radar, Sonar & Navigation.
- Radar, Sonar & Navigation
- Language:
- English
- Subjects (All):
- Detectors.
- Doppler radar.
- Imaging.
- Machine learning.
- Radar.
- Signal processing--Digital techniques--Data processing.
- Signal processing.
- Synthetic aperture radar.
- Target acquisition.
- Physical Description:
- 1 online resource (420 pages).
- Place of Publication:
- Stevenage : SciTech Publishing Incorporated, 2020.
- System Details:
- text file
- Summary:
- 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 machine learning; and Theoretical foundations of deep learning. The second part covers Special topics and following topics are dealt with: Radar data representation for classification of activities of daily living; Challenges in training DNNs for classification of radar micro-Doppler signatures; and Machine learning techniques for SAR data augmentation. The third part deals with Applications and covers the following topics: Classifying micro-Doppler signatures using deep convolutional neural networks; Deep neural network design for SAR/ISAR-based automatic target recognition; Deep learning for passive synthetic aperture radar imaging; Fusion of deep representations in multistatic radar networks; and Application of deep learning to radar remote sensing.
- ISBN:
- 9781785618536
- Access Restriction:
- Restricted for use by site license.
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