| Description |
1 online resource (378 pages) |
| Summary |
Learn about the most recent theoretical and practical advances in radar signal processing using tools and techniques from compressive sensing. Providing a broad perspective that fully demonstrates the impact of these tools, the accessible and tutorial-like chapters cover topics such as clutter rejection, CFAR detection, adaptive beamforming, random arrays for radar, space-time adaptive processing, and MIMO radar. Each chapter includes coverage of theoretical principles, a detailed review of current knowledge, and discussion of key applications, and also highlights the potential benefits of using compressed sensing algorithms. A unified notation and numerous cross-references between chapters make it easy to explore different topics side by side. Written by leading experts from both academia and industry, this is the ideal text for researchers, graduate students and industry professionals working in signal processing and radar |
| Notes |
Title from publisher's bibliographic system (viewed on 02 Oct 2019) |
| Subject |
Pattern perception.
|
|
Machine learning.
|
|
Computer science.
|
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Signal processing -- Communications
|
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Electronic Data Processing
|
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Machine Learning
|
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Computer science
|
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Machine learning
|
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Pattern perception
|
| Form |
Electronic book
|
| Author |
De Maio, Antonio., editor
|
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Eldar, Yonina C., editor
|
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Haimovich, Alexander M., editor
|
| ISBN |
9781108552653 |
|
110855265X |
|
