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Название: Robust Network Compressive Sensing
Автор: Guangtao Xue, Yi-Chao Chen, Feng Lyu
Издательство: Springer
Серия: SpringerBriefs in Computer Science
Год: 2022
Страниц: 99
Язык: английский
Формат: pdf (true), epub
Размер: 25.2 MB
This book investigates compressive sensing techniques to provide a robust and general framework for network data analytics. The goal is to introduce a compressive sensing framework for missing data interpolation, anomaly detection, data segmentation and activity recognition, and to demonstrate its benefits. The primary audience for this book is data engineers, analysts and researchers, who need to deal with Big Data with missing anomalous and synchronization problems. Advanced level students focused on compressive sensing techniques will also benefit from this book as a reference.
Автор: Guangtao Xue, Yi-Chao Chen, Feng Lyu
Издательство: Springer
Серия: SpringerBriefs in Computer Science
Год: 2022
Страниц: 99
Язык: английский
Формат: pdf (true), epub
Размер: 25.2 MB
This book investigates compressive sensing techniques to provide a robust and general framework for network data analytics. The goal is to introduce a compressive sensing framework for missing data interpolation, anomaly detection, data segmentation and activity recognition, and to demonstrate its benefits. The primary audience for this book is data engineers, analysts and researchers, who need to deal with Big Data with missing anomalous and synchronization problems. Advanced level students focused on compressive sensing techniques will also benefit from this book as a reference.