Compressive Sensing for Wireless Communication

Compressed Sensing (CS) is a promising method that recovers the sparse and compressible signals from severely under-sampled measurements. CS can be applied to wireless communication to enhance its capabilities. As this technology is proliferating, it is possible to explore its need and benefits for...

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Detalles Bibliográficos
Autor principal: Sankararajan, Radha (-)
Otros Autores: Rajendran, Hemalatha, Sukumaran, Aasha Nandhini
Formato: Libro electrónico
Idioma:Inglés
Publicado: Aalborg : River Publishers 2016.
Colección:EBSCO Academic eBook Collection Complete.
River Publishers Series in Communications.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b47413128*spi
Descripción
Sumario:Compressed Sensing (CS) is a promising method that recovers the sparse and compressible signals from severely under-sampled measurements. CS can be applied to wireless communication to enhance its capabilities. As this technology is proliferating, it is possible to explore its need and benefits for emerging applicationsCompressive Sensing for Wireless Communication provides: A clear insight into the basics of compressed sensing A thorough exploration of applying CS to audio, image and computer vision Different dimensions of applying CS in Cognitive radio networks CS in wireless sensor network for spatial compression and projection Real world problems/projects that can be implemented and tested Efficient methods to sample and reconstruct the images in resource constrained WMSN environmentThis book provides the details of CS and its associated applications in a thorough manner. It lays a direction for students and new engineers and prepares them for developing new tasks within the field of CS. It is an indispensable companion for practicing engineers who wish to learn about the emerging areas of interest.
Descripción Física:1 recurso electrónico
Formato:Forma de acceso: World Wide Web.
ISBN:9788793379862
9781003337652
9781000794366
9781000791228