The shapes of if-part fuzzy sets affect the approximating capability of fuzzy systems. In this paper, the fuzzy systems with the kernel-shaped if-part fuzzy sets are built directly from the training data. It is proved that these fuzzy systems are universal approximators and their uniform approximation rates can be estimated in the single-input–single-output (SISO) case. On the basis of these ra...

The purpose of this paper is to study the problem of pattern classification as this is presented in the context of data mining. Among the various approaches we focus on the use of Fuzzy Logic for pattern classification, due to its close relation to human thinking. More specifically, this paper presents a heuristic fuzzy method for the classification of numerical data, followed by the design and...

The present paper is a humble attempt to develop a fuzzy function approximator which can completely self-generate its fuzzy rule base and input-output membership functions from an input-output data set. The fuzzy system can be further adapted to modify its rule base and output membership functions to provide satisfactory performance. This proposed scheme, called generalised influential rule sea...

Neural Networks (NN), Type-1 Fuzzy Logic Systems (T1FLS) and Interval Type-2 Fuzzy Logic Systems (IT2FLS) are universal approximators, they can approximate any non-linear function. Recent research shows that embedding T1FLS on an NN or embedding IT2FLS on an NN can be very effective for a wide number of non-linear complex systems, especially when handling imperfect information. In this paper we...

G4-FET has attracted attention as an emerging device for the future generations of semiconductor industry. This paper is intended to propose a model representing the characteristics of G4FET device in order to perform circuit simulations. The modeling approach is established upon the neuro-fuzzy technique whose main strength is that they are universal approximators with the ability to solicit i...

Abstract: We propose and analyze a robust adaptive fuzzy controller for nonlinear systems without a priori knowledge of the sign of the input gain function. No assumptions are made about the type of nonlinearities of the system, except that such nonlinearities are smooth. The uncertain nonlinearities are captured by the fuzzy systems that have been proven to be universal approximators. The prop...

Methods to build function approximators from example data have gained considerable interest in the past. Especially methodologies that build models that allow an interpretation have attracted attention. Most existing algorithms, however, are either complicated to use or infeasible for high-dimensional problems. This article presents an ecient and easy to use algorithm to construct fuzzy graphs...

Adaptive fuzzy systems are usefull universal function approximators. But they suffer from the curse of dimensionality. I.e. the number of parameters, which have to be tuned, increases drastically if the number of input variables increases. This has the effect that memory and computational demands increase also drastically, and more stringently fitting problems may occur if the number of trainin...

Takagi–Sugeno (TS) fuzzy systems have been employed as fuzzy controllers and fuzzy models in successfully solving difficult control and modeling problems in practice. Virtually all the TS fuzzy systems use linear rule consequent. At present, there exist no results (qualitative or quantitative) to answer the fundamentally important question that is especially critical to TS fuzzy systems as fuzz...