Compressed Sensing for Engineers

Compressed Sensing (CS) is a theory that recovers a sparse signal from an under-determined system of linear equations. It has practical applications in reducing scan time in Magnetic Resonance Imaging and X-Ray Computed CT, making scans more feasible for pediatric and geriatric subjects. This book is a valuable resource for engineering students in signal processing and requires a basic understanding of signal processing and linear algebra.

Format: Paperback / softback
Length: 292 pages
Publication date: 13 June 2022
Publisher: Taylor & Francis Ltd

Compressed Sensing (CS) is a fascinating field that addresses the challenge of recovering a sparse signal from an under-determined system of linear equations. This topic holds immense practical significance, as all naturally occurring signals can be sparsely represented in some domain. Over the past few years, CS has made remarkable strides in reducing scan time in Magnetic Resonance Imaging (MRI), making it more feasible for pediatric and geriatric subjects. It has also played a crucial role in reducing health hazards in X-Ray Computed CT scans.

This comprehensive book is an invaluable resource for engineering students interested in signal processing. It assumes a basic understanding of signal processing and linear algebra, providing a solid foundation for further exploration. The book covers fundamental concepts of compressed sensing, making the subject matter accessible to engineers at various levels. It delves into algorithms such as group-sparsity and row-sparsity, which are crucial in compressing data while preserving important information.

Furthermore, the book showcases applications of CS in computational imaging, medical imaging, biomedical signal processing, and machine learning. It includes MATLAB examples that facilitate further development and understanding of the concepts presented. By leveraging the power of CS, researchers and practitioners can efficiently extract valuable information from data, leading to advancements in various fields.

In conclusion, this book is a must-read for engineering students and professionals seeking to delve into the world of compressed sensing. Its comprehensive coverage, accessible language, and practical examples make it an invaluable resource for anyone interested in advancing their knowledge in this field.

Weight: 540g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032338712