Signal Processing and Networking for Big Data Applications

ISBN-13: 9781107124387 / Twarda / 2017 / 474 str.

Opis

This unique text helps make sense of big data using signal processing techniques, in applications including machine learning, networking, and energy systems.

Recenzje

'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

Spis treści

Part I. Overview of Big Data Applications: 1. Introduction; 2. Data parallelism: the supporting architecture; Part II. Methodology and Mathematical Background: 3. First order methods; 4. Sparse optimization; 5. Sublinear algorithms; 6. Tensor for big data; 7. Deep learning and applications; Part III. Big Data Applications: 8. Compressive sensing based big data analysis; 9. Distributed large-scale optimization; 10. Optimization of finite sums; 11. Big data optimization for communication networks; 12. Big data optimization for smart grid systems; 13. Processing large data set in MapReduce; 14. Massive data collection using wireless sensor networks.