## Simplifying fuzzy rule-based models using orthogonal transformation methods

- John Yen, Liang Wang
- IEEE Trans. Systems, Man, and Cybernetics, Part B
- 1999

@article{Su2009ANR, title={A novel rule antecedent structure and its identification for fuzzy models}, author={Ming Su and R. Russell Rhinehart}, journal={2009 American Control Conference}, year={2009}, pages={4272-4277} }

- Published 2009 in 2009 American Control Conference

The existing combinatorial antecedent structure in fuzzy models makes them suffer from “the curse of dimensionality”. In this work, a novel rule antecedent structure is proposed to design an efficient fuzzy model by using fewer rules. The new rule antecedent only uses nonlinear variables. Additionally, the proposed rule antecedents are expressed as ellipsoids covering the underlying local regions, which make spatial coverage more efficient.