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Sparse Representations for Radar with MATLAB Examples [electronic resource] / by Peter Knee.

By: Knee, Peter [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Synthesis Lectures on Algorithms and Software in Engineering: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2012Edition: 1st ed. 2012.Description: XIII, 71 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031015199.Subject(s): Signal processing | Signal, Speech and Image ProcessingAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 621,382 Online resources: Click here to access online
Contents:
Radar Systems: A Signal Processing Perspective -- Introduction to Sparse Representations -- Dimensionality Reduction -- Radar Signal Processing Fundamentals -- Sparse Representations in Radar.
In: Springer Nature eBookSummary: Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB® examples to emphasize the practical implementations both inside and outside the radar field. Table of Contents: Radar Systems: A Signal Processing Perspective / Introduction to Sparse Representations / Dimensionality Reduction / Radar Signal Processing Fundamentals / Sparse Representations in Radar.
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Radar Systems: A Signal Processing Perspective -- Introduction to Sparse Representations -- Dimensionality Reduction -- Radar Signal Processing Fundamentals -- Sparse Representations in Radar.

Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB® examples to emphasize the practical implementations both inside and outside the radar field. Table of Contents: Radar Systems: A Signal Processing Perspective / Introduction to Sparse Representations / Dimensionality Reduction / Radar Signal Processing Fundamentals / Sparse Representations in Radar.

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