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Fault Detection in Analog Circuits Using a Fuzzy Dendritic Cell Algorithm

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Artificial Immune Systems (ICARIS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6825))

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Abstract

This work presents the early stages of the development of a fault detection system based on the Dendritic Cell Algorithm. The system is designed to detect parametric faults in linear time invariant circuits. The safe signal is related to the mean square error between the PAA representations of the impulse responses of the circuit under test and the golden circuit. The danger signal is related to the variation of that error. Instead of using a weighted sum with fixed weights, a fuzzy inference system (FIS) is used, since it is easier to define linguistic rules to infer the combination of the signals than to find appropriate weight values.

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Author information

Authors and Affiliations

  1. Dept. of Electronics and Telecommunications Engineering, Rio de Janeiro State University, 20550-013, Rio de Janeiro, RJ, Brazil

    Jorge L. M. Amaral

Authors
  1. Jorge L. M. Amaral
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Editor information

Editors and Affiliations

  1. Computer Laboratory, University of Cambridge, William Gates Building, 15 JJ Thomson Avenue, CB3 0FD, Cambridge, UK

    Pietro Liò

  2. Department of Mathematics and Computer Science, University of Catania, Viale A. Doria, 6, 95125, Catania, Italy

    Giuseppe Nicosia

  3. Chair for IT Security (I20), Technische Universität München, Boltzmannstraße 3, 85748, Garching, Germany

    Thomas Stibor

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Amaral, J.L.M. (2011). Fault Detection in Analog Circuits Using a Fuzzy Dendritic Cell Algorithm. In: Liò, P., Nicosia, G., Stibor, T. (eds) Artificial Immune Systems. ICARIS 2011. Lecture Notes in Computer Science, vol 6825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22371-6_26

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  • DOI: https://doi.org/10.1007/978-3-642-22371-6_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22370-9

  • Online ISBN: 978-3-642-22371-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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