FAULT TOLERANT SMALL-WORLD CELLULAR NEURAL NETWORKS FOR INTERMITTED FAULTS
Keywords:
Fault Tolerance, Cellular Neural Networks, Small-World Networks, Small- World Cellular Neural NetworksAbstract
A Cellular Neural Network (CNN) is a neural network model linked only to neighbor- hoods and which is suitable for image processing, such as noise reduction and edge detection. A Small World Cellular Neural Network (SWCNN) is an extended CNN to which has been added a small world link, which is a global short-cut. The SWCNN has better performance than the CNN. One of the weaknesses of the SWCNN has low fault tolerance. If the the neuron is failed, the SWCNN shows lower fault tolerance than the CNN. Previously, we proposed TMR and Reliability Counter (RC) for fault tolerance the SWCNN. In this paper, we propose the Stateful Reliability Counter (Stateful RC) method to improve tolerance. The Stateful RC has a failure state of the last histrory. The Stateful RC for TMR has higher fault tolerant than TMR and RC in the low repaire rate.
Downloads
References
L. O. Chua and L. Yang, “Cellular neural networks: theory,” IEEE Trans. Circuits Syst., vol. 35,
no. 10, pp. 1257-1272, 1988.
K. Tsuruta, Z. Yang, Y. Nishio, and A. Ushida, “Small-world cellular neural networks for image
processing applications,” European Conference on Circuit Theory and Design, vol. 1, pp. 225-228,
D. J. Watts and S. H. Strogatz, “Collective dynamics of ‘small-world‘ networks,” Nature, vol. 393,
pp. 440-442, 1998.
M. E. J. Newman, “The structure and function of complex networks,” SIAM Review, vol. 45, no.
, pp. 167-256, 2003.
D. K. Pradhan, Fault-tolerant computing system design. Prentice Hall PTR, 1996.
M. Abd-El-Barr, Design and Analysis of Reliable and Fault-Tolerant Computer System. Imperial
College Press, 2007
K. Matsumoto, M. Uehara, and H. Mori, “Fault tolerant small-world cellular neural networks,” in
Proc. 4th Int. Symp. Frontiers in Networking with Applications (FINA2008), 2008, pp. 168-172.
K. Matsumoto, H. Mori, and M. Uehara, “Fault tolerance in small-world cellular neural networks
for image processing,” in Proc. 21st Int. Conf. Advanced Information Networking and Applications,
vol. 1, 2007, pp. 835-839.
K.Matsumoto, H.Mori, andM. Uehara, “Fault tolerance for small-world cellular neural networks,”
in Network-Based Information Systems (NBIS2008), Springer LNCS, vol. 5186, 2008, pp.223-231.