Volume 26 Issue 2
Feb.  2000
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MAO Jian-qin, ZHANG Jian-gang, DAI Ji-yang, et al. Approximate Limit Sampling Data Using Fuzzy-Tree Model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2000, 26(2): 231-234. (in Chinese)
Citation: MAO Jian-qin, ZHANG Jian-gang, DAI Ji-yang, et al. Approximate Limit Sampling Data Using Fuzzy-Tree Model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2000, 26(2): 231-234. (in Chinese)

Approximate Limit Sampling Data Using Fuzzy-Tree Model

  • Received Date: 14 Oct 1998
  • Publish Date: 29 Feb 2000
  • A linear binary fuzzy tree structure approach, i.e. Fuzzy-Tree model, is proposed for complex nonlinear system modeling. In comparison with some other modeling approaches, such as ANFIS and Neural Network model, the proposed model is of less computation, higher accuracy, especially insensitivity to high dimension. It is proved that for any square integrated continuous function, there always exists a Fuzzy-Tree model to approximate it arbitrarily. Fuzzy-Tree model simulates the layered decision-making and piece-wise linearized processing procedure for solving complex problems. A numerical solution was given to show the approach.

     

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  • [1] Takagi T, Sugeno M. Fuzzy identification of systems and applications to modelling and control[J]. IEEE Trans on System Man and Cyb, 1985,1(1):116~132. [2]Jang J S R. ANFIS:adaptive-network-based fuzzy inference system[J]. IEEE Trans on System Man and Cyb, 1993, 23(3):665~685. [3]Gelfand S B, Ravishankar C S. A tree-structured piecewise linear adaptive filter[J]. IEEE Trans on Info Theory, 1993, 39(6):1907~1922.
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