• 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