Wow! eBook
Deep Learning for Radar and Communications Automatic Target Recognition Unabridged Edition
Author(s): Uttam K. Majumder (Author), Erik P. Blasch (Author), David A. Garren (Author)
- Publisher: Artech House
- Publication Date: 31 Aug. 2020
- Edition: Unabridged
- Language: English
- Print length: 300 pages
- ISBN-10: 163081637X
- ISBN-13: 9781630816377
Book Description
This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues.
Editorial Reviews
About the Author
Erik P. Blasch is a program officer at the United States Air Force Research Laboratory (AFRL) Air Force Office of Scientific Research (AFOSR). He received Ph.D. in electrical engineering from Wright State University. He is a Fellow of IEEE. Uttam K. Majumder is a senior electronics engineer at the United States Air Force Research Laboratory (AFRL). He received his Ph.D. in electrical engineering from Purdue University. He is a senior member of IEEE. David A. Garren is a professor at the Naval Postgraduate School. He received his Ph.D. from the College of William and Mary. He is a senior member of IEEE.
