this paper is pertained with the problem of admissibility analysis of uncertain discrete-time nonlinear singular systems by adopting the state-space takagi-sugeno fuzzy model with time-delays and norm-bounded parameter uncertainties. lyapunov krasovskii functionals are constructed to obtain delay-dependent stability condition in terms of linear matrix inequalities, which is dependent on the low...

The Takagi-Sugeno (TS) fuzzy rule system is a widely used data mining technique, and is of particular use in the identification of non-linear interactions between variables. However the number of rules increases dramatically when applied to high dimensional data sets (the curse of dimensionality). Few robust methods are available to identify important rules while removing redundant ones, and th...

In this paper, a parameter estimation problem for a Takagi-Sugeno (TS) fuzzy dynamical system is formulated under the assumption that the premises in the membership functions are known. A linear expression in consequent parameters is obtained under this assumption. If the system is timevarying (TV), the parameters can be determined by recursive estimation techniques. As an alternate approach, t...

We study the filter design problem for Takagi-Sugeno fuzzy systems which are subject to norm-bounded uncertainties in each subsystem. As we know that the Takagi-Sugeno fuzzy linear systems can be used to represent smooth nonlinear systems, the studied plants can also be uncertain complex systems. We suppose to design a filter with the order of the original system which is also dependent on the ...

Answering a question of Kuniba, Misra, Okado, Takagi, and Uchiyama, it is shown that certain Demazure characters of affine type A, coincide with the graded characters of coordinate rings of closures of conjugacy classes of nilpotent matrices.

It is shown that the Takagi-Sugeno-Kang (TSK) fuzzy inference mechanism is optimal with respect to a certain criterion that quantiies the controversy between the inference made, and the knowledge represented in the knowledge-base.

In this paper a global linearization of fuzzy model is given. The parameters of global linear model are obtained by instantaneous linearization of fuzzy model. The model is given in the form of the Sugeno-Takagi fuzzy model.