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“Sloppy Engineering” and the Olfactory System of Insects

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Biologically Inspired Signal Processing for Chemical Sensing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 188))

Abstract

Research on nervous systems has had an important influence on new information processing paradigms and has led to the invention of artificial neural networks in the past. In recent work we have analyzed the olfactory pathway of insects as a pattern classification device with unstructured (random) connectivity. In this chapter I will review these and related results and discuss the implications for applications in artificial olfaction. As we will see, successful classification depends on appropriate connectivity degrees and activation thresholds, as well as large enough numbers of neurons, because the strategy essentially rests on the law of large numbers. Taken as an inspiration for artificial olfaction, the analysis suggests a new paradigm of random kernel methods for odour and general pattern classification.

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Authors and Affiliations

  1. Centre for Computational Neuroscience and Robotics, University of Sussex, Falmer, Brighton, BN1 9QJ, UK

    Thomas Nowotny

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  1. Thomas Nowotny
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  1. Departament d’Electronica, Universitat de Barcelona , Martí i Franqués 1, 08028, Barcelona, Spain

    Agustín Gutiérrez

  2. Departament d’Electronica, Universitat de Barcelona, Martí i Franqués 1, 08028, Barcelona, Spain

    Santiago Marco

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Nowotny, T. (2009). “Sloppy Engineering” and the Olfactory System of Insects. In: Gutiérrez, A., Marco, S. (eds) Biologically Inspired Signal Processing for Chemical Sensing. Studies in Computational Intelligence, vol 188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00176-5_1

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  • DOI: https://doi.org/10.1007/978-3-642-00176-5_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00175-8

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