Journal article

Stability of hierarchical fuzzy systems generated by Neuro-Fuzzy

R Saad, SK Halgamuge

SOFT COMPUTING | SPRINGER | Published : 2004


Hierarchical implementation provides a way of retaining the interpretability of a fuzzy system when the number of inputs to the system is very high. Existing Neuro-Fuzzy systems capable of constructing fuzzy systems from training data do not address this issue and restrict to the generation of single layer fuzzy systems. This paper first defines a generic hierarchical fuzzy system that can be implemented exploiting the recursion supported by standard programming languages. Secondly it shows that hierarchical fuzzy systems can be generated from a specialised multi-layer perceptron neural network using a heuristic rule extraction algorithm. Finally, the paper provides a proof for the stability..

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University of Melbourne Researchers