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10.1109/WAINA.2009.70guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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Fault Tolerance Small-World Cellular Neural Networks for Inttermitted Faults

Published: 26 May 2009 Publication History

Abstract

A Cellular Neural Network (CNN) is a neural network model in which cells are linked only to neighboring cells. In image processing, a CNN can be used for noise reduction and edge detection. Small-World Cellular Neural Networks (SWCNN) are CNNs extended by adding a small-world link, which is a global short-cut. Although SWCNNs have better performance than CNNs, one of the weaknesses of the SWCNN is fault tolerance. Previously, we proposed multiple SWCNN layers to improve the fault tolerance of the SWCNN. However, as this only addresses termination failures it is not sufficient. In this paper, we propose a Time Stamp Voting method to improve tolerance of intermittent faults. This method is superior to Triple Modular Redundancy (TMR).
  1. Fault Tolerance Small-World Cellular Neural Networks for Inttermitted Faults

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      Published In

      cover image Guide Proceedings
      WAINA '09: Proceedings of the 2009 International Conference on Advanced Information Networking and Applications Workshops
      May 2009
      1193 pages
      ISBN:9780769536392

      Publisher

      IEEE Computer Society

      United States

      Publication History

      Published: 26 May 2009

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      1. Fault Tolerant
      2. Small-World Cellular Neural Networks

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