Signal processing for big data [From the Guest Editors]

Georgios B. Giannakis, Francis Bach, Raphael Cendrillon, Michael Mahoney, Jennifer Neville

Research output: Contribution to journalEditorialpeer-review

17 Scopus citations

Abstract

The articles in this special section delineate the theoretical and algorithmic nderpinnings 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.

Original languageEnglish (US)
Article number6879633
Pages (from-to)15-16
Number of pages2
JournalIEEE Signal Processing Magazine
Volume31
Issue number5
DOIs
StatePublished - Sep 2014

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