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Novel convolution-based signal processing techniques for an artificial olfactory mucosa

By J. W. Gardner and J. E. Taylor

Abstract

As our understanding of the human olfactory system has grown, so has our ability to design artificial devices that mimic its functionality, so called electronic noses (e-noses). This has led to the development of a more sophisticated biomimetic system known as an artificial olfactory mucosa (e-mucosa) that comprises a large distributed sensor array and artificial mucous layer. In order to exploit fully this new architecture, new approaches are required to analyzing the rich data sets that it generates. In this paper, we propose a novel convolution based approach to processing signals from the e-mucosa. Computer simulations are performed to investigate the robustness of this approach when subjected to different real-world problems, such as sensor drift and noise. Our results demonstrate a promising ability to classify odors from poor sensor signals

Topics: TK
Publisher: Institute of Electrical and Electronic Engineers
Year: 2009
OAI identifier: oai:wrap.warwick.ac.uk:2255

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Citations

  1. (2006). A dimensionality-reduction technique inspired by receptor convergence in the olfactory system,” Sens. doi
  2. (1973). Chromatographic separation of odorantsbythenose:Retentiontimesmeasuredacrossinvivoolfactory mucosa,” doi
  3. (2003). Electronic nosefor space program applications,” doi
  4. (1999). Electronic Noses: Principles and Applications. doi
  5. (2007). Finiteelementsimulationofabiomimeticolfactorymicrosystemforspatio-temporal signal generation,” AsiaSim doi
  6. (2002). M.Bicego,G.Tessari,G.Tecchiolli,andM.Bettinelli,“Acomparative analysis of basic pattern recognition techniques for the development of small size electronic nose,” Sens. doi
  7. (2004). Monitoring space shuttle air quality using the jet propulsion laboratory electronic nose,” doi
  8. (2005). Smart Chemical Sensing: Towards a Nose-on-a-Chip,”
  9. (1997). Smell: The Secret Seducer. doi
  10. (1955). The Convolution Transform.

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