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Optimization of Max-Plus based Neural Networks using Genetic Algorithms  

Han, Chang-Wook (동의대학교 전기공학과)
Publication Information
Journal of the Institute of Convergence Signal Processing / v.14, no.1, 2013 , pp. 57-61 More about this Journal
Abstract
A hybrid genetic algorithm based learning method for the morphological neural networks (MNN) is proposed. The morphological neural networks are based on max-plus algebra, therefore, it is difficult to optimize the coefficients of MNN by the learning method with derivative operations. In order to solve the difficulty, a hybrid genetic algorithm based learning method to optimize the coefficients of MNN is used. Through the image compression/reconstruction experiment using test images extracted from standard image database(SIDBA), it is confirmed that the quality of the reconstructed images obtained by the proposed method is better than that obtained by the conventional neural networks.
Keywords
Genetic Algorithms; Morphological Neural Networks; Image Compression/Reconstruction;
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Times Cited By KSCI : 1  (Citation Analysis)
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