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  3. Signal Processing and Networking for Big Data Applications
  • Cited by 35
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    • Publisher:
      Cambridge University Press
      Publication date:
      May 2017
      April 2017
      ISBN:
      9781316408032
      9781107124387
      DOI:
      https://doi.org/10.1017/9781316408032
      Dimensions:
      (247 x 174 mm)
      Weight & Pages:
      0.89kg, 474 Pages
      Dimensions:
      Weight & Pages:
      • Subjects:
      Communications and Signal Processing, Engineering, Computer Science, Communications, Information Theory and Security
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    Subjects:
    Communications and Signal Processing, Engineering, Computer Science, Communications, Information Theory and Security
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    Book description

    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.

    Reviews

    'A very nice balanced treatment over two large-scale signal processing aspects: mathematical backgrounds versus big data applications, with a strong flavor of distributed optimization and computation.'

    Shuguang Cui - University of California, Davis

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