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# IEEE Transactions on Fuzzy Systems

## Filter Results

Displaying Results 1 - 21 of 21

Publication Year: 2011, Page(s): C1
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• ### IEEE Transactions on Fuzzy Systems publication information

Publication Year: 2011, Page(s): C2
| PDF (42 KB)
• ### Seclusion-Factor Method to Solve Fuzzy-Multiple Criteria Decision-Making Problems

Publication Year: 2011, Page(s):201 - 209
Cited by:  Papers (13)
| | PDF (401 KB) | HTML

This paper incorporates the basic concepts of subjectivity with the objective of decision theory to develop a method which intellectualizes ambiguity into multiple-criteria decision-making (MCDM) problems. An outranking intensity is introduced to determine the degree of overall outranking between competing alternatives, which are represented by fuzzy numbers. The comparison of these degrees is mad... View full abstract»

• ### Scalable TSK Fuzzy Modeling for Very Large Datasets Using Minimal-Enclosing-Ball Approximation

Publication Year: 2011, Page(s):210 - 226
Cited by:  Papers (42)
| | PDF (2422 KB) | HTML

In order to overcome the difficulty in Takagi-Sugeno-Kang (TSK) fuzzy modeling for large datasets, scalable TSK (STSK) fuzzy-model training is investigated in this study based on the core-set-based minimal-enclosing-ball (MEB) approximation technique. The specified L2-norm penalty-based -insensitive criterion is first proposed for TSK-model training, and it is found that such TSK fuzzy-model train... View full abstract»

• ### An Enhanced Type-Reduction Algorithm for Type-2 Fuzzy Sets

Publication Year: 2011, Page(s):227 - 240
Cited by:  Papers (69)
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Karnik and Mendel proposed an algorithm to compute the centroid of an interval type-2 fuzzy set efficiently. Based on this algorithm, Liu developed a centroid type-reduction strategy to carry out type reduction for type-2 fuzzy sets. A type-2 fuzzy set is decomposed into a collection of interval type-2 fuzzy sets by -cuts. Then, the Karnik-Mendel algorithm is called for each interval type-2 fuzzy ... View full abstract»

• ### Top-Down Induction of Fuzzy Pattern Trees

Publication Year: 2011, Page(s):241 - 252
Cited by:  Papers (26)
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Fuzzy pattern tree induction was recently introduced as a novel machine learning method for classification. Roughly speaking, a pattern tree is a hierarchical, tree-like structure, whose inner nodes are marked with generalized (fuzzy) logical operators and whose leaf nodes are associated with fuzzy predicates on input attributes. A pattern-tree classifier is composed of an ensemble of such pattern... View full abstract»

• ### Information Granularity in Fuzzy Binary GrC Model

Publication Year: 2011, Page(s):253 - 264
Cited by:  Papers (58)
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Zadeh's seminal work in theory of fuzzy-information granulation in human reasoning is inspired by the ways in which humans granulate information and reason with it. This has led to an interesting research topic: granular computing (GrC). Although many excellent research contributions have been made, there remains an important issue to be addressed: What is the essence of measuring a fuzzy-informat... View full abstract»

• ### Robust Adaptive Fuzzy Control by Backstepping for a Class of MIMO Nonlinear Systems

Publication Year: 2011, Page(s):265 - 275
Cited by:  Papers (78)
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This paper presents a robust adaptive control method for a class of multi-input-multi-output (MIMO) nonlinear systems that are transformable to a parametric-strict-feedback form which has couplings among input channels and the appearance of parametric uncertainties in the input matrices. The proposed approach effectively combines the design techniques of robust adaptive control by backstepping and... View full abstract»

• ### Decentralized Fuzzy Control of Nonlinear Interconnected Dynamic Delay Systems via Mixed $H_2/!H_infty$ Optimization With Smith Predictor

Publication Year: 2011, Page(s):276 - 290
Cited by:  Papers (14)
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Each subsystem of a nonlinear interconnected dynamic delayed system is approximated by a weighted combination of L transfer function delayed systems (TFDSs). The H2-norm of the difference between the transfer function of a reference model and the closed-loop transfer function of the kth TFDS of subsystem i is then minimized to obtain a suitable frequency response without incurring oscil... View full abstract»

• ### Integrated Fault Estimation and Accommodation Design for Discrete-Time Takagi–Sugeno Fuzzy Systems With Actuator Faults

Publication Year: 2011, Page(s):291 - 304
Cited by:  Papers (92)
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This paper addresses the problem of integrated robust fault estimation (FE) and accommodation for discrete-time Takagi-Sugeno (T-S) fuzzy systems. First, a multiconstrained reduced-order FE observer (RFEO) is proposed to achieve FE for discrete-time T-S fuzzy models with actuator faults. Based on the RFEO, a new fault estimator is constructed. Then, using the information of online FE, a new approa... View full abstract»

• ### ANCFIS: A Neurofuzzy Architecture Employing Complex Fuzzy Sets

Publication Year: 2011, Page(s):305 - 322
Cited by:  Papers (46)
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Complex fuzzy sets (CFSs) are an extension of type-1 fuzzy sets in which the membership of an object to the set is a value from the unit disc of the complex plane. Although there has been considerable progress made in determining the properties of CFSs and complex fuzzy logic, there has yet to be any practical application of this concept. We present the adaptive neurocomplex-fuzzy-inferential syst... View full abstract»

• ### Control Synthesis of T–S Fuzzy Systems Based on a New Control Scheme

Publication Year: 2011, Page(s):323 - 338
Cited by:  Papers (38)
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This paper studies the control synthesis problem of Takagi-Sugeno (T--S) fuzzy systems. By splitting the premise variable spaces and using the properties of fuzzy sets, a new control scheme is proposed based on a new class of fuzzy Lyapunov functions, and a convex condition for designing fuzzy controllers is given, where the new fuzzy Lyapunov functions and fuzzy controllers are constructed based ... View full abstract»

• ### A TS-Type Maximizing-Discriminability-Based Recurrent Fuzzy Network for Classification Problems

Publication Year: 2011, Page(s):339 - 352
Cited by:  Papers (31)
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This work proposes a Takagi-Sugeno (TS)-type maximizing-discriminability-based recurrent fuzzy network (MDRFN) that can classify highly confusable patterns. The discriminative capability plays a significant role in determining classification performance. To increase the discriminative capability, the proposed MDRFN considers minimum classification error (MCE) and minimum training error (MTE). In M... View full abstract»

• ### $H_{\infty }$ Filtering For Nonlinear Discrete-Time Systems Subject to Quantization and Packet Dropouts

Publication Year: 2011, Page(s):353 - 365
Cited by:  Papers (69)
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This paper investigates the problem of H∞ filtering for a class of nonlinear discrete-time systems with measurement quantization and packet dropouts. Each output is transmitted via an independent communication channel, and the phenomenon of packet dropouts in transmission is governed by an individual random binary distribution, while the quantization errors are treated as sector-... View full abstract»

• ### Model Approximation for Discrete-Time State-Delay Systems in the T–S Fuzzy Framework

Publication Year: 2011, Page(s):366 - 378
Cited by:  Papers (210)
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This paper is concerned with the problem of H∞ model approximation for discrete-time Takagi-Sugeno (T-S) fuzzy time-delay systems. For a given stable T- S fuzzy system, our attention is focused on the construction of a reduced-order model, which not only approximates the original system well in an H∞ performance but is also translated into a linear lower dimensi... View full abstract»

• ### Evolutionary-Group-Based Particle-Swarm-Optimized Fuzzy Controller With Application to Mobile-Robot Navigation in Unknown Environments

Publication Year: 2011, Page(s):379 - 392
Cited by:  Papers (62)
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This paper proposes an evolutionary-group-based particle-swarm-optimization (EGPSO) algorithm for fuzzy-controller (FC) design. The EGPSO uses a group-based framework to incorporate crossover and mutation operations into particle-swarm optimization. The EGPSO dynamically forms different groups to select parents in crossover operations, particle updates, and replacements. An adaptive velocity-mutat... View full abstract»

• ### A New Fuzzy Impulsive Control of Chaotic Systems Based on T–S Fuzzy Model

Publication Year: 2011, Page(s):393 - 398
Cited by:  Papers (32)
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In this paper, fuzzy impulsive control is used for stabilization of chaotic systems based on the Takagi-Sugeno (T-S) model. The stability issue of the general nonlinear impulsive control system is first investigated via comparison criterion. Then, a novel impulsive control scheme is presented for chaotic systems based on the T-S fuzzy model. Some sufficient conditions are given to stabilize the T-... View full abstract»

Publication Year: 2011, Page(s): 399
| PDF (320 KB)

Publication Year: 2011, Page(s): 400
| PDF (203 KB)
• ### IEEE Computational Intelligence Society Information

Publication Year: 2011, Page(s): C3
| PDF (37 KB)
• ### IEEE Transactions on Fuzzy Systems Information for authors

Publication Year: 2011, 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