Influences of Perturbations of Training Pattern Pairs on Fuzzy Morphological Associative Memory Networks
ZENG Shui-Ling1,2,XU Wei-Hong1,2,YANG Jing-Yu1
1.College of Computer Science and Technology,Nanjing University of Science and Technology,Nanjing 210094 2.College of Mathematics and Computer Science,Jishou University,Jishou 416000
Abstract Two kinds of morphological associative memory networks are analyzed by scholars and they have almost the same good fault-tolerant abilities of erosive/dilative noise. In this paper, the investigation reveals that two kinds of networks have different robustness to perturbation of training patterns. The robustness is good to one kind of fuzzy morphological associative memory network, and the property of the other kind is relatively poor. The conclusions offer guidance for the learning algorithm selection of the neural networks and the acquisition process of the previous training patterns.
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2010, Vol. 23 
