In the present paper a Korovkin-type theorem is proposed for the approximation operators defined by the inverse Ftransforms. These results allow us to choose between a variety of shapes to be used as atoms of the fuzzy partitions used within the F-transform’s framework. In this way we can enlarge considerably the class of F-transforms proposed recently by I. Perfilieva. The new fuzzy partitions...

In the present work, by applying known Bernstein polynomials and their advantageous properties, we establish an efficient iterative algorithm to approximate the numerical solution of fuzzy Fredholm integral equations of the second kind. The convergence of the proposed method is given and the numerical examples illustrate that the proposed iterative algorithm are ‎valid.‎

Received 20 April 2010; revised 14 August 2010; accepted 29 August 2010. ———————————————————————————————Abstract In this paper, we present a numerical method for solving fully fuzzy polynomials. The proposed method is based on approximating fuzzy neural network. This method can also lead to improving numerical methods. In this work, an architecture of fuzzy neural networks is also proposed to f...

Obtaining Interpretable Fuzzy Models from Fuzzy Clustering and Fuzzy Regression* Frank Hiippner Frank Klawonn University of Applied Sciences, Emden Department of Electrical Engineering and Computer Science Constantiaplatz 4 D-26723 Emden, Germany e-mail alias: [email protected] In this paper we develop an objective finctionbased clustering algorithm to build fizzy models of the Takagi-Sug...

Many researchers have been interested in approximation properties of fuzzy logic systems (FLS), which like neural networks can be seen as approximation schemes. Almost all of them tackled Mamdani fuzzy model, which was shown to have many interesting features. This paper aims to present alternatives for traditional inference mechanisms and CRI method. The most attractive advantage of these new m...

Many researchers have been interested in approximation properties of fuzzy logic systems (FLS), which like neural networks can be seen as approximation schemes. Almost all of them tackled Mamdani fuzzy model, which was shown to have many interesting features. This paper aims to present alternatives for traditional inference mechanisms and CRI method. The most attractive advantage of these new m...

| A formalism for coding fuzzy models of dynam-ical systems is presented. It is shown that the formalism is rich enough to capture the performance of arbitrary conventional discrete time dynamical systems, whose transition maps are polynomials with rational coeecients. The proof of this fact provides a constructive algorithm for generating fuzzy models to approximate an arbitrary map on a compa...

Fuzzy polynomial equations (FPEs) don’t have algebraic solutions, generally. In this paper, we first, express and prove some relationships between Husdroof meter and length function on classes of triangular fuzzy numbers. We appraise the behavior of fuzzy polynomials by using the length function properties. Next, we transform a FPE into a generalized fuzzy polynomial equation (GFPE) and introdu...

A neuro-fuzzy system for character recognition using a fuzzy Hough transform technique is presented in this paper. For each character pattern, membership values are determined for a number of fuzzy sets defined on the standard Hough transform accumulator cells. These basic fuzzy sets are combined by t-norms to synthesize additional fuzzy sets whose heights form an ndimensional feature vector fo...

This study introduces an information granular-based fuzzy radial basis function neural networks (FRBFNN) based on multiobjective optimization and weighted least square (WLS). An improved multiobjective space search algorithm (IMSSA) is proposed to optimize the FRBFNN. In the design of FRBFNN, the premise part of the rules is constructed with the aid of Fuzzy C-Means (FCM) clustering while the c...