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Signal Processing and Networking for Big Data Applications
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  • Cited by 3
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    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Omotere, Oluwaseyi Qian, Lijun Jantti, Riku Pan, Miao and Han, Zhu 2017. Big RF Data Assisted Cognitive Radio Network Coexistence in 3.5GHz Band. p. 1.

    Zhang, Yuchao Li, Yusen Xu, Ke Wang, Dan Li, Minghui Cao, Xuan and Liang, Qingqing 2017. A Communication-Aware Container Re-Distribution Approach for High Performance VNFs. p. 1555.

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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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