Coding theory for reliable signal processing

Aditya Vempaty, Yunghsiang S. Han, Lav R. Varshney, Pramod K. Varshney

Research output: Contribution to conferencePaperpeer-review


With increased dependence on technology in daily life, there is a need to ensure their reliable performance. There are many applications where we carry out inference tasks assisted by signal processing systems. A typical system performing an inference task can fail due to multiple reasons: presence of a component with permanent failure, a malicious component providing corrupt information, or there might simply be an unreliable component which randomly provides faulty data. Therefore, it is important to design systems which perform reliably even in the presence of such unreliable components. Coding theory based techniques provide a possible solution to this problem. In this position paper, we survey some of our recent work on the use of coding theory based techniques for the design of some signal processing applications. As examples, we consider distributed classification and target localization in wireless sensor networks. We also consider the more recent paradigm of crowdsourcing and discuss how coding based techniques can be used to mitigate the effect of unreliable crowd workers in the system.

Original languageEnglish (US)
Number of pages6
StatePublished - 2014
Externally publishedYes
Event2014 International Conference on Computing, Networking and Communications, ICNC 2014 - Honolulu, HI, United States
Duration: Feb 3 2014Feb 6 2014


Other2014 International Conference on Computing, Networking and Communications, ICNC 2014
Country/TerritoryUnited States
CityHonolulu, HI


  • Coding theory
  • Crowdsourcing
  • Distributed Inference
  • Reliability
  • Wireless Sensor Networks

ASJC Scopus subject areas

  • Computer Networks and Communications


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