DocumentCode :
33296
Title :
Signal Processing for Big Data [From the Guest Editors]
Author :
Giannakis, Georgios B. ; Bach, F. ; Cendrillon, Raphael ; Mahoney, Marshall ; Neville, Jennifer
Volume :
31
Issue :
5
fYear :
2014
fDate :
Sept. 2014
Firstpage :
15
Lastpage :
16
Abstract :
The articles in this special section delineate the theoretical and algorithmic underpinnings along with the relevance of signal processing tools to the emerging field of big data and introduce readers to the challenges and opportunities for SP research on (massive-scale) data analytics. The latter entails an extended and continuously refined technological wish list, which is envisioned to encompass high-dimensional, decentralized, parallel, online, and robust statistical signal processing as well as large, distributed, fault-tolerant, and intelligent systems engineering. The goal is to selectively sample a diverse gamut of big data challenges and opportunities through surveys of methodological advances, as well as more focused- and application-oriented contributions chosen on the basis of timeliness, importance, and relevance to signal processing.
Keywords :
Big data; Data mining; Data processing; Information technology; Internet; Signal processing algorithms; Social network services; Special issues and sections;
fLanguage :
English
Journal_Title :
Signal Processing Magazine, IEEE
Publisher :
ieee
ISSN :
1053-5888
Type :
jour
DOI :
10.1109/MSP.2014.2330054
Filename :
6879633
Link To Document :
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