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Mathematical Problems in Engineering
Volume 2013, Article ID 614543, 9 pages
http://dx.doi.org/10.1155/2013/614543
Research Article

Robust Template Decomposition without Weight Restriction for Cellular Neural Networks Implementing Arbitrary Boolean Functions Using Support Vector Classifiers

1Department of Information Engineering, I-Shou University, Kaohsiung 84001, Taiwan
2Department of Electrical Engineering, I-Shou University, Kaohsiung 84001, Taiwan

Received 10 April 2013; Accepted 20 May 2013

Academic Editor: Ker-Wei Yu

Copyright © 2013 Yih-Lon Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [2 citations]

The following is the list of published articles that have cited the current article.

  • Yih-Lon Lin, Jer-Guang Hsieh, and Jyh-Horng Jeng, “Robust decomposition with guaranteed robustness for cellular neural networks implementing an arbitrary Boolean function,” Neurocomputing, 2014. View at Publisher · View at Google Scholar
  • Xiaoliang Zhang, Lequan Min, and Min Li, “Robust design of dilation and erosion CNN for gray scale image,” Proceedings of SPIE - The International Society for Optical Engineering, vol. 9794, 2015. View at Publisher · View at Google Scholar