By Topic

# IEEE Transactions on Fuzzy Systems

## Filter Results

Displaying Results 1 - 20 of 20

Publication Year: 2005, Page(s): c1
| PDF (32 KB)
• ### IEEE Transactions on Fuzzy Systems publication information

Publication Year: 2005, Page(s): c2
| PDF (38 KB)
• ### Interval Fuzzy Model Identification Using$l_infty$-Norm

Publication Year: 2005, Page(s):561 - 568
Cited by:  Papers (26)
| | PDF (473 KB) | HTML

In this paper, we present a new method of interval fuzzy model identification. The method combines a fuzzy identification methodology with some ideas from linear programming theory. We consider a finite set of measured data, and we use an optimality criterion that minimizes the maximum estimation error between the data and the proposed fuzzy model output. The idea is then extended to modeling the ... View full abstract»

• ### A Novel Fuzzy System With Dynamic Rule Base

Publication Year: 2005, Page(s):569 - 582
Cited by:  Papers (19)
| | PDF (484 KB) | HTML

A new fuzzy system containing a dynamic rule base is proposed in this paper. The novelty of the proposed system is in the dynamic nature of its rule base which has a fixed number of rules and allows the fuzzy sets to dynamically change or move with the inputs. The number of the rules in the proposed system can be small, and chosen by the designer. The focus of this article is mainly on the approxi... View full abstract»

• ### Fuzzy Clustering for Data Time Arrays With Inlier and Outlier Time Trajectories

Publication Year: 2005, Page(s):583 - 604
Cited by:  Papers (27)
| | PDF (926 KB) | HTML

In many knowledge discovery and data mining tasks, fuzzy clustering is one of the most common tools for data partitioning. In this paper dynamic fuzzy clustering models for classifying a set of multivariate time trajectories (time series, sequences) are developed. In particular, by adopting an exploratory approach, based on a geometric-algebraic formulation of the data time array, different kinds ... View full abstract»

• ### Design of a New Fuzzy Suction Controller Using Fuzzy Modeling for Nonlinear Boundary Layer

Publication Year: 2005, Page(s):605 - 616
Cited by:  Papers (8)
| | PDF (658 KB) | HTML

There are two types of fuzzy modeling: 1) imitating an expert experiment or fulfilling an engineering knowledge, and 2) modeling a complex or unknown system. In this paper, based on the first type of fuzzy modeling, a new fuzzy suction controller (NFSC) is proposed using its linguistic rules to design nonlinear boundary layer. Two kinds of nonlinear boundary layers are discussed. The first kind is... View full abstract»

• ### Fuzzy Measure and Probability Distributions: Distorted Probabilities

Publication Year: 2005, Page(s):617 - 629
Cited by:  Papers (23)
| | PDF (488 KB) | HTML

This work studies fuzzy measures and their application to data modeling. We focus on the particular case when fuzzy measures are distorted probabilities. We analyze their properties and introduce a new family of measures (m-dimensional distorted probabilities). The work finishes with the application of two dimensional distorted probabilities to a modeling problem. Results of the application of suc... View full abstract»

• ### Delay-Dependent Stability Analysis and Controller Synthesis for Discrete-Time T&#8211;S Fuzzy Systems With Time Delays

Publication Year: 2005, Page(s):630 - 643
Cited by:  Papers (76)
| | PDF (524 KB) | HTML

Based on a novel delay-dependent piecewise Lyapunov-Krasovskii functional (DPLKF), this paper presents delay-dependent stability analysis and synthesis methods for discrete-time Takagi-Sugeno (T-S) fuzzy systems with time delays. It is shown that the stability and stabilization with some required performance can be established for the closed loop control system if there exists a DPLKF and that the... View full abstract»

• ### A Consensus Support System Model for Group Decision-Making Problems With Multigranular Linguistic Preference Relations

Publication Year: 2005, Page(s):644 - 658
Cited by:  Papers (260)
| | PDF (616 KB) | HTML

The group decision-making framework with linguistic preference relations is studied. In this context, we assume that there exist several experts who may have different background and knowledge to solve a particular problem and, therefore, different linguistic term sets (multigranular linguistic information) could be used to express their opinions. The aim of this paper is to present a model of con... View full abstract»

• ### Approximation Capabilities of Hierarchical Fuzzy Systems

Publication Year: 2005, Page(s):659 - 672
Cited by:  Papers (50)
| | PDF (432 KB) | HTML

Derived from practical application in location analysis and pricing, and based on the approach of hierarchical structure analysis of continuous functions, this paper investigates the approximation capabilities of hierarchical fuzzy systems. By first introducing the concept of the natural hierarchical structure, it is proved that continuous functions with natural hierarchical structure can be natur... View full abstract»

• ### A Characteristic-Point-Based Fuzzy Inference Classifier by a Closeness Matrix

Publication Year: 2005, Page(s):673 - 687
Cited by:  Papers (3)
| | PDF (833 KB) | HTML

In this paper, a characteristic-point-based fuzzy inference classifier (CPFIC) is proposed to perform two-class classification. Through fuzzy interpolation, a subset of classified samples can be taken as representatives of all samples. They are called characteristic points (CPs). A closeness matrix representing the closeness of two samples in a same class is proposed in selecting CPs. By solving a... View full abstract»

• ### A Probabilistic Quantifier Fuzzification Mechanism: The Model and Its Evaluation for Information Retrieval

Publication Year: 2005, Page(s):688 - 700
Cited by:  Papers (16)
| | PDF (653 KB) | HTML

In this paper, we propose a new quantifier fuzzification mechanism which is deeply rooted in the theory of probability. This quantifier fuzzification mechanism skips the nested assumption, which is inherent to other probabilistic quantification methods. The new quantification approach complies with the properties required for determiner fuzzification schemes (DFS) with finite sets and, hence, its ... View full abstract»

• ### Digitalizing a Fuzzy Observer-Based Output-Feedback Control: Intelligent Digital Redesign Approach

Publication Year: 2005, Page(s):701 - 716
Cited by:  Papers (44)
| | PDF (668 KB) | HTML

This paper concerns an intelligent digital redesign (IDR) technique for a Takagi-Sugeno fuzzy observer-based output-feedback control (FOBOFC) system. The term IDR involves converting an existing analog control into an equivalent digital counterpart in the sense of state-matching. The IDR problem is herein viewed as a minimization problem of the norm distances between nonlinearly interpolated linea... View full abstract»

• ### A New Convergence Proof of Fuzzy c-Means

Publication Year: 2005, Page(s):717 - 720
Cited by:  Papers (37)
| | PDF (186 KB) | HTML

In this letter, we give a new, more direct derivation of the convergence properties of the fuzzy c-means (FCM) algorithm, using the equivalence between the original and reduced FCM criterion. From the point of view of the reduced criterion, the FCM algorithm is simply a steepest descent algorithm with variable steplength. We prove that steplength adjustment follows from the majorization principle ... View full abstract»

• ### 2006 IEEE World Congress on Computational Intelligence

Publication Year: 2005, Page(s): 721
| PDF (650 KB)

Publication Year: 2005, Page(s): 722
| PDF (318 KB)

Publication Year: 2005, Page(s): 723
| PDF (218 KB)
• ### Join IEEE

Publication Year: 2005, Page(s): 724
| PDF (322 KB)
• ### IEEE Computational Intelligence Society Information

Publication Year: 2005, Page(s): c3
| PDF (32 KB)
• ### IEEE Transactions on Fuzzy Systems Information for authors

Publication Year: 2005, Page(s): c4
| PDF (29 KB)

## Aims & Scope

The IEEE Transactions on Fuzzy Systems (TFS) is published bimonthly. TFS will consider papers that deal with the theory, design or an application of fuzzy systems ranging from hardware to software.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Jonathan Garibaldi
University of Nottingham
Nottingham NG8 1BB, U.K.
jon.garibaldi@nottingham.ac.uk
Phone: +44 115 95 14216
Fax: +44 115 95 14799