Fuzzy self-organizing map: mechanism and convergence

This paper presents the learning mechanism of a model of fuzzy neural network, fuzzy self-organizing map (FSOM). The analysis on the convergence of learning mechanism will be elucidated. When the dimension of input data is one, we can prove that the convergence of the learning mechanism is almost sure. While the input data dimension is higher than one, the mechanism fulfils only the necessary condition for convergence. Simulation result will be given to illustrate the model.<<ETX>>

[1]  Teuvo Kohonen,et al.  Self-organization and associative memory: 3rd edition , 1989 .

[2]  James C. Bezdek,et al.  Fuzzy models—What are they, and why? [Editorial] , 1993, IEEE Transactions on Fuzzy Systems.

[3]  James C. Bezdek,et al.  A Review of Probabilistic, Fuzzy, and Neural Models for Pattern Recognition , 1996, J. Intell. Fuzzy Syst..

[4]  James C. Bezdek,et al.  Fuzzy Kohonen clustering networks , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[5]  Lennart Ljung,et al.  Analysis of recursive stochastic algorithms , 1977 .

[7]  Chi-Cheng Jou FUZZY COUNTERPROPAGATION NETWORKS , 1995 .

[8]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[9]  I︠a︡. Z. T︠S︡ypkin,et al.  Foundations of the theory of learning systems , 1973 .