Signal processing and networking for big data applications

Zhu Han, Mingyi Hong, Dan Wang

Research output: Authored / edited bookResearch book or monograph (as author)Academic researchpeer-review

22 Citations (Scopus)

Abstract

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. The first comprehensive book on the use of signal processing for big data applications. Covers a wide range of techniques for design, analysis and optimization. Discusses applications in areas such as machine learning, networking and energy systems.

Original languageEnglish
PublisherCambridge University Press
Number of pages362
ISBN (Electronic)9781316408032
ISBN (Print)9781107124387
DOIs
Publication statusPublished - 27 Apr 2017

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science(all)

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