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Signal processing and networking for big data applications / Zhu Han, Mingyi Hong, Dan Wang

By: Contributor(s): Material type: TextTextPublication details: New York : Cambridge University Press, c2017.Description: xii, 362 p. : ill. ; 26 cmISBN:
  • 9781107124387
Subject(s): DDC classification:
  • 005.7 HA SI
Online resources: Summary: This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.
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Holdings
Item type Current library Call number Status Date due Barcode
REGULAR University of Wollongong in Dubai Main Collection 005.7 HA SI (Browse shelf(Opens below)) Available T0056551

Includes bibliographical references and index.

This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.

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