Computational complexity of hierarchical fuzzy systems

The computational complexity of a conventional fuzzy system (CFS) and hierarchical fuzzy systems without defuzzification (HFSs w/o DF) are analysed in terms of the electronic components needed to construct a computational circuit to calculate the intermediate outputs between layers and to carry out crisp output from the last layer in the hierarchy. Furthermore, two different types of HFS w/o DF are discussed, providing more options to which they are optimally suited with the characteristics of the original CFS.

[1]  Yasuyuki Kojima,et al.  Neural networks designed on Ap-proximate Reasoning Architecture , 1991 .

[2]  Herbert Taub,et al.  Digital Integrated Electronics , 1976 .

[3]  R. Lai,et al.  Designing a hierarchical fuzzy logic controller using differential evolution , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[4]  David J. Comer.  Introduction to Semiconductor Circuit Design , 1968 .

[5]  C. S. George Lee,et al.  Reinforcement structure/parameter learning for neural-network-based fuzzy logic control systems , 1994, IEEE Trans. Fuzzy Syst..

[6]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[7]  Jun Zhou,et al.  Hierarchical fuzzy control , 1991 .

[8]  Saman K. Halgamuge,et al.  Self-evolving neural networks for rule-based data processing , 1997, IEEE Trans. Signal Process..

[9]  Martin Hartley Jones,et al.  A practical introduction to electronic circuits , 1977 .

[10]  John Sum,et al.  Fuzzy self-organizing map: mechanism and convergence , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[11]  Li-Xin Wang,et al.  A Course In Fuzzy Systems and Control , 1996 .

[12]  Allan R. Hambley,et al.  Electronics: A Top-Down Approach to Computer-Aided Circuit Design , 1994 .

[13]  Brian Holdsworth,et al.  Digital Logic Design , 1981 .