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Design of RBF Network Based on Fuzzy Clustering Method for Modeling of Respiratory System

  • Kouji Maeda
  • Shunshoku Kanae
  • Zi-Jiang Yang
  • Kiyoshi Wada
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)

Abstract

Pulmonary elastance provides an important basis for deciding air pressure parameters of mechanical ventilators, and airway resistance is an important parameter in the diagnosis of respiratory diseases. The authors have proposed a second order nonlinear differential equation model of respiratory system whose elastic and resistant coefficients are expressed by RBF networks with the lung volume as the input. When we use RBF networks expression, numerical stability can be expected, because the output of each node is in range of [0,1], the balance between each node is good. However, the problems of deciding the number of nodes and the center/deviation of each node were remained. In this paper, a design method of RBF network based on fuzzy clustering method is proposed to decide center and deviation of each node. By means of fuzzy clustering, the available data set is partitioned into fuzzy subsets so that each RBF works effectively. The proposed method is validated by examples of application to practical clinical data.

Keywords

Fuzzy Cluster Airway Resistance Fuzzy Subset Respiration Treatment Partition Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Maeda, K., Kanae, S., Yang, Z.J., Wada, K.: Estimation of Respiratory Parameters Based on RBF Network. In: The 23rd SICE Kyushu Branch Annual Conference, December 4–5, pp. 133–136. Kitakyushu Science and Research Park (2004)Google Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kouji Maeda
    • 1
  • Shunshoku Kanae
    • 1
  • Zi-Jiang Yang
    • 1
  • Kiyoshi Wada
    • 1
  1. 1.Department of Electrical and Electronic Systems Engineering, Graduate School of Information Science and Electrical EngineeringKyushu University, Email:jin@ees.kyushu-u.ac.jpFukuokaJapan

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