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http://dx.doi.org/10.9708/jksci.2011.16.6.061

A study on the Fuzzy Recurrent Neural Networks for the image noise elimination filter  

Byun, Oh-Sung (R&D Center, HYUNDAI MOBIS)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.6, 2011 , pp. 61-70 More about this Journal
Abstract
In this paper, it is realized an image filter for a noise elimination using a recurrent neural networks with fuzzy. The proposed fuzzy neural networks structure is to converge weights and the number of iteration for a certain value by using basically recurrent neural networks structure and is simplified computation and complexity of mathematics by applying the hybrid fuzzy membership function operator. In this paper, the proposed method, the recurrent neural networks applying fuzzy which is collected a certain value, has been proved improving average 0.38dB than the conventional method, the generalied recurrent neural networks, by using PSNR. Also, a result image of the proposed method was similar to the original image than a result image of the conventional method by comparing to visual images.
Keywords
Fuzzy Membership Function; Filter; Fuzzy Recurrent Neural Networks; Sigmoid Function; Noise Elimination;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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