• Title/Summary/Keyword: Immunotronic system

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A New Immunotronic Approach to Hardware Fault Detection Using Symbiotic Evolution (공생 진화를 이용한 Immunotronic 접근 방식의 하드웨어 오류 검출)

  • Lee, Sang-Hyung;Kim, Eun-Tai;Lee, Hee-Jin;Park, Mignon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.42 no.5
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    • pp.59-68
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    • 2005
  • A novel immunotronic approach to fault detection in hardware based on symbiotic evolution is proposed in this paper. In the immunotronic system, the generation of tolerance conditions corresponds to the generation of antibodies in the biological immune system. In this paper, the principle of antibody diversity, one of the most important concepts in the biological immune system, is employed and it is realized through symbiotic evolution. Symbiotic evolution imitates the generation of antibodies in the biological immune system morethan the traditional GA does. It is demonstrated that the suggested method outperforms the previous immunotronic methods with less running time. The suggested method is applied to fault detection in a decade counter (typical example of finite state machines) and MCNC finite state machines and its effectiveness is demonstrated by the computer simulation.

A Biologically Inspired New Hardware Fault Detection: immunotronic and Genetic Algorithm-Based Approach

  • Lee, Sanghyung;Kim, Euntai;Park, Mignon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.1
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    • pp.7-11
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    • 2004
  • This paper proposes a new immunotronic approach for the fault detection in hardware. The suggested method is, inspired by biology and its implementation is based on genetic algorithm. Tolerance conditions in the immunotronic system for fault detection correspond to the antibodies in the biological immune system. A novel algorithm of generating tolerance conditions is suggested based on the principle of the antibody diversity and GA optimization is employed to select mature tolerance conditions in immunotronic fault detection system. The suggested method is applied to the fault detection for MCNC benchmark FSMs (finite state machines) and its effectiveness is demonstrated by the computer simulation.