Hierarchical fuzzy relational models: linguistic interpretation and universal approximation

Hierarchical fuzzy structures composed of a series of sub-models connected in cascade have been found to be effective tools for dealing with the dimensionality problem in fuzzy systems. This paper addresses both the issues of linguistic interpretation and universal approximation of systems using hierarchical fuzzy models. Fuzzy relational equations are used to implement the sub-models of a hierarchical structure that has two very important properties: i) it can be converted into a completely equivalent nonhierarchical model, which in turn allows the extraction of linguistic knowledge in the form of consistent fuzzy If-Then rules; and ii) it is a universal approximator. These properties are analytically derived and the proposed model is illustrated by means of an example.

[1]  Li-Xin Wang,et al.  Analysis and design of hierarchical fuzzy systems , 1999, IEEE Trans. Fuzzy Syst..

[2]  Alexander Graham,et al.  Kronecker Products and Matrix Calculus: With Applications , 1981 .

[3]  Mokhtar S. Bazaraa,et al.  Nonlinear Programming: Theory and Algorithms , 1993 .

[4]  L X Wang,et al.  Fuzzy basis functions, universal approximation, and orthogonal least-squares learning , 1992, IEEE Trans. Neural Networks.

[5]  W.C. Amaral,et al.  Hierarchical fuzzy relational models: linguistic interpretation and universal approximation , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[6]  José Valente de Oliveira,et al.  Towards neuro-linguistic modeling: Constraints for optimization of membership functions , 1999, Fuzzy Sets Syst..

[7]  Ricardo J. G. B. Campello,et al.  Modeling and linguistic knowledge extraction from systems using fuzzy relational models , 2001, Fuzzy Sets Syst..

[8]  D. Willaeys,et al.  THE USE OF FUZZY SETS FOR THE TREATMENT OF FUZZY INFORMATION BY COMPUTER , 1993 .

[9]  W. Rudin Principles of mathematical analysis , 1964 .

[10]  Witold Pedrycz,et al.  An Introduction to Fuzzy Sets , 1998 .

[11]  Witold Pedrycz Identification in fuzzy systems , 1984, IEEE Transactions on Systems, Man, and Cybernetics.

[12]  Li-Xin Wang,et al.  Universal approximation by hierarchical fuzzy systems , 1998, Fuzzy Sets Syst..

[13]  D. Luenberger Optimization by Vector Space Methods , 1968 .

[14]  W. Brockmann,et al.  Function approximation with decomposed fuzzy systems , 1999, Fuzzy Sets Syst..

[15]  Ricardo J. G. B. Campello,et al.  Optimization of hierarchical neural fuzzy models , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

[16]  Korris Fu-Lai Chung,et al.  On multistage fuzzy neural network modeling , 2000, IEEE Trans. Fuzzy Syst..

[17]  Ronald R. Yager,et al.  Essentials of fuzzy modeling and control , 1994 .

[18]  M. Tismenetsky,et al.  Kronecker Products and Matrix Calculus (Alexander Graham) , 1983 .

[19]  Witold Pedrycz,et al.  Fuzzy control and fuzzy systems , 1989 .

[20]  Hongxing Li,et al.  Hierarchical TS fuzzy system and its universal approximation , 2005, Inf. Sci..

[21]  Robert Babuska,et al.  Fuzzy Modeling for Control , 1998 .

[22]  Korris Fu-Lai Chung,et al.  Multilevel fuzzy relational systems: structure and identification , 2002, Soft Comput..

[23]  Li-Xin Wang,et al.  A note on universal approximation by hierarchical fuzzy systems , 2000, Inf. Sci..

[24]  Shyh Hwang,et al.  An identification algorithm in fuzzy relational systems , 1996, Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium.

[25]  Ricardo J. G. B. Campello,et al.  Towards true linguistic modelling through optimal numerical solutions , 2003, Int. J. Syst. Sci..

[26]  W. Pedrycz,et al.  An introduction to fuzzy sets : analysis and design , 1998 .

[27]  T. Fukuda,et al.  Self-tuning fuzzy modeling with adaptive membership function, rules, and hierarchical structure based on genetic algorithm , 1995 .

[28]  Jin S. Lee,et al.  Universal approximation by hierarchical fuzzy system with constraints on the fuzzy rule , 2002, Fuzzy Sets Syst..

[29]  Ming-Ling Lee,et al.  Modeling of hierarchical fuzzy systems , 2003, Fuzzy Sets Syst..

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