When Compressive Sensing Meets Mobile Crowdsensing

This book provides a comprehensive introduction to applying compressive sensing to improve data quality in the context of mobile crowdsensing. It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user privacy, and detecting false data. Mobile crowd...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Kong, Linghe (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Wang, Bowen (http://id.loc.gov/vocabulary/relators/aut), Chen, Guihai (http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Introduction
  • Mathematical Theory of Compressive Sensing
  • Basic Compressive Sensing for Data Reconstruction
  • Bayesian Compressive Sensing for Task Allocation
  • Adaptive Compressive Sensing for Incentive Mechanism
  • Encoded Compressive Sensing for Privacy Preservation
  • Iterative Compressive Sensing for Fault Detection
  • Conclusion.