Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Online ISSN : 2188-4749
Print ISSN : 2188-4730
第37回ISCIE「確率システム理論と応用」国際シンポジウム(2005年10月, 大阪茨木)
Medical Image Recognition by Revised GMDH-type Neural Network Algorithm with a Feedback Loop Identifying Sigmoid Function Neural Network
Tadashi Kondo
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2006 年 2006 巻 p. 143-148

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In this paper, the revised Group Method of Data Handling (GMDH)-type neural network algorithm with a feedback loop identifying sigmoid function neural network is applied to the medical image recognition of the brain. This revised GMDH-type neural network automatically selects the structural parameters such as the number of neurons in each layer, the number of feedback loops and the useful input variables by using Akaike's Information Criterion (AIC) or Prediction Sum of Squares (PSS) criterion. It is shown that this revised GMDH-type neural network is a very useful method for the medical image recognition because the neural network architecture is automatically organized so as th minimize AIC or PSS criterion.
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© 2006 ISCIE Symposium on Stochastic Systems Theory and Its Applications
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