Signal processing and networking for big data applications:
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...
Gespeichert in:
| Beteilige Person: | |
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| Weitere beteiligte Personen: | , |
| Format: | E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2017
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| Links: | https://doi.org/10.1017/9781316408032 |
| Zusammenfassung: | 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. |
| Umfang: | 1 Online-Ressource (xii, 362 Seiten) |
| ISBN: | 9781316408032 |
Internformat
MARC
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| 100 | 1 | |a Han, Zhu |d 1974- | |
| 245 | 1 | 0 | |a Signal processing and networking for big data applications |c Zhu Han, University of Houston, Mingyi Hong, Iowa State University, Dan Wang, the Hong Kong Polytechnic University |
| 264 | 1 | |a Cambridge |b Cambridge University Press |c 2017 | |
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| 520 | |a 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. | ||
| 700 | 1 | |a Hong, Mingyi | |
| 700 | 1 | |a Wang, Dan | |
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Datensatz im Suchindex
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| id | ZDB-20-CTM-CR9781316408032 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-17T11:17:16Z |
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| isbn | 9781316408032 |
| language | English |
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| spelling | Han, Zhu 1974- Signal processing and networking for big data applications Zhu Han, University of Houston, Mingyi Hong, Iowa State University, Dan Wang, the Hong Kong Polytechnic University Cambridge Cambridge University Press 2017 1 Online-Ressource (xii, 362 Seiten) txt c cr 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. Hong, Mingyi Wang, Dan Erscheint auch als Druck-Ausgabe 9781107124387 |
| spellingShingle | Han, Zhu 1974- Signal processing and networking for big data applications |
| title | Signal processing and networking for big data applications |
| title_auth | Signal processing and networking for big data applications |
| title_exact_search | Signal processing and networking for big data applications |
| title_full | Signal processing and networking for big data applications Zhu Han, University of Houston, Mingyi Hong, Iowa State University, Dan Wang, the Hong Kong Polytechnic University |
| title_fullStr | Signal processing and networking for big data applications Zhu Han, University of Houston, Mingyi Hong, Iowa State University, Dan Wang, the Hong Kong Polytechnic University |
| title_full_unstemmed | Signal processing and networking for big data applications Zhu Han, University of Houston, Mingyi Hong, Iowa State University, Dan Wang, the Hong Kong Polytechnic University |
| title_short | Signal processing and networking for big data applications |
| title_sort | signal processing and networking for big data applications |
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