IEEE Transactions on Fuzzy Systems

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Publication Year: 2009, Page(s): C1
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• IEEE Transactions on Fuzzy Systems publication information

Publication Year: 2009, Page(s): C2
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• Why Fuzzy Decision Trees are Good Rankers

Publication Year: 2009, Page(s):1233 - 1244
Cited by:  Papers (24)
| | PDF (837 KB) | HTML

Several fuzzy extensions of decision tree induction, which is an established machine-learning method, have already been proposed in the literature. So far, however, fuzzy decision trees have almost exclusively been used for the performance task of classification. In this paper, we show that a fuzzy extension of decision trees is arguably more useful for another performance task, namely ranking. Ro... View full abstract»

• Concept of Linguistic Variable-Based Fuzzy Ensemble Approach: Application to Interlaced HDTV Sequences

Publication Year: 2009, Page(s):1245 - 1258
Cited by:  Papers (29)
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This paper addresses the problem of edge restoration in digital images. Taking advantage of an ensemble approach, multiple type-1 fuzzy filters are combined to reach a decision. The fuzzy logic concept for linguistic variables and possibility theory is discussed with regard to knowledge representation and inference procedures. To improve conventional deinterlacing issues, we adopt type-1 fuzzy set... View full abstract»

• Fuzzy Regression Models Using the Least-Squares Method Based on the Concept of Distance

Publication Year: 2009, Page(s):1259 - 1272
Cited by:  Papers (27)
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Fuzzy regression models are developed to construct the relationship between explanatory variables and responses in a fuzzy environment. In order to increase the explanatory performance of the model, the least-squares method is applied to determine the numeric coefficients based on the concept of distance. Unlike most existing approaches, the numeric coefficients in the proposed model can have nega... View full abstract»

• Building Confidence-Interval-Based Fuzzy Random Regression Models

Publication Year: 2009, Page(s):1273 - 1283
Cited by:  Papers (32)
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In real-world regression analysis, statistical data may be linguistically imprecise or vague. Given the co-existence of stochastic and fuzzy uncertainty, real data cannot be characterized by using only the formalism of random variables. In order to address regression problems in the presence of such hybrid uncertain data, fuzzy random variables are introduced in this study to serve as an integral ... View full abstract»

• Polynomial Fuzzy Models for Nonlinear Control: A Taylor Series Approach

Publication Year: 2009, Page(s):1284 - 1295
Cited by:  Papers (97)
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Classical Takagi-Sugeno (T-S) fuzzy models are formed by convex combinations of linear consequent local models. Such fuzzy models can be obtained from nonlinear first-principle equations by the well-known sector-nonlinearity modeling technique. This paper extends the sector-nonlinearity approach to the polynomial case. This way, generalized polynomial fuzzy models are obtained. The new class of mo... View full abstract»

• SOFMLS: Online Self-Organizing Fuzzy Modified Least-Squares Network

Publication Year: 2009, Page(s):1296 - 1309
Cited by:  Papers (69)
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In this paper, an online self-organizing fuzzy modified least-square (SOFMLS) network is proposed. The algorithm has the ability to reorganize the model and adapt itself to a changing environment where both the structure and learning parameters are performed simultaneously. The network generates a new rule if the smallest distance between the new data and all the existing rules (the winner rule) i... View full abstract»

• A Design of Genetically Oriented Fuzzy Relation Neural Networks (FrNNs) Based on the Fuzzy Polynomial Inference Scheme

Publication Year: 2009, Page(s):1310 - 1323
Cited by:  Papers (5)
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In this paper, we introduce new architectures of genetically oriented fuzzy relation neural networks (FrNNs) and offer a comprehensive design methodology that supports their development. The proposed FrNNs are based on ldquoif-thenrdquo-rule-based networks, with the extended structure of the premise and the consequence parts of the individual rules. We consider two types of the FrNN topologies, wh... View full abstract»

• Robust Controllability of T–S Fuzzy-Model-Based Control Systems With Parametric Uncertainties

Publication Year: 2009, Page(s):1324 - 1335
Cited by:  Papers (15)
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The robust controllability problem for the Takagi-Sugeno (T-S) fuzzy-model-based control systems is studied in this paper. Under the assumption that the nominal T-S fuzzy-model-based control systems are locally controllable (i.e., each fuzzy rule of the nominal T-S fuzzy-model-based control systems has a full row rank for its controllability matrix), a sufficient condition is proposed to preserve ... View full abstract»

• Generalized Receding Horizon Control of Fuzzy Systems Based on Numerical Optimization Algorithm

Publication Year: 2009, Page(s):1336 - 1352
Cited by:  Papers (17)
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The optimal control of fuzzy systems with constraints is still an open problem. Our focus concerns the optimal control problem of fuzzy systems derived from receding horizon control (RHC) schemes. We consider methods to numerically compute the value function for general fuzzy systems. The numerical method that is developed using the finite difference with sigmoidal transformation is a stable and c... View full abstract»

• Latticized Linear Optimization on the Unit Interval

Publication Year: 2009, Page(s):1353 - 1365
Cited by:  Papers (15)
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This paper considers the latticized linear optimization (LLO) problem and its variants, which are a special class of optimization problems constrained by fuzzy relational equations or inequalities. We show that an optimal solution to such a problem can be obtained in polynomial time as long as the objective function is a max-separable function with continuous monotone components. We further show t... View full abstract»

• Computing the Numerical Scale of the Linguistic Term Set for the 2-Tuple Fuzzy Linguistic Representation Model

Publication Year: 2009, Page(s):1366 - 1378
Cited by:  Papers (80)
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When using linguistic approaches to solve decision problems, we need the techniques for computing with words (CW). Together with the 2-tuple fuzzy linguistic representation models (i.e., the Herrera and Martinez model and the Wang and Hao model), some computational techniques for CW are also developed. In this paper, we define the concept of numerical scale and extend the 2-tuple fuzzy linguistic ... View full abstract»

• An Evolving Fuzzy Neural Network Based on the Mapping of Similarities

Publication Year: 2009, Page(s):1379 - 1396
Cited by:  Papers (6)
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Evolving fuzzy systems (EFSs) use online learning to extract knowledge from data, perform a high-level adaptation of the network structure, and learn parameters. In this paper, we describe the performance of an EFS that is called similarity mapping, where the training pairs (xi and zi) are compressed into input and output clusters. The predictive error is minimized using a pr... View full abstract»

• Perceptual Reasoning for Perceptual Computing: A Similarity-Based Approach

Publication Year: 2009, Page(s):1397 - 1411
Cited by:  Papers (33)
| | PDF (1370 KB) | HTML

Perceptual reasoning (PR) is an approximate reasoning method that can be used as a computing-with-words (CWW) engine in perceptual computing. There can be different approaches to implement PR, e.g., firing-interval-based PR (FI-PR), which has been proposed in J. M. Mendel and D. Wu, IEEE Trans. Fuzzy Syst., vol. 16, no. 6, pp. 1550-1564, Dec. 2008 and similarity-based PR (S-PR), which is pr... View full abstract»

• Weighted Fuzzy Interpolative Reasoning Based on Weighted Increment Transformation and Weighted Ratio Transformation Techniques

Publication Year: 2009, Page(s):1412 - 1427
Cited by:  Papers (36)
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In this paper, we present a new weighted fuzzy interpolative reasoning method for sparse fuzzy rule-based systems. The proposed method uses weighted increment transformation and weighted ratio transformation techniques to handle weighted fuzzy interpolative reasoning in sparse fuzzy rule-based systems. It allows each variable that appears in the antecedent parts of fuzzy rules to associate with a ... View full abstract»

• Decentralized $H_{infty }$ Filter Design for Discrete-Time Interconnected Fuzzy Systems

Publication Year: 2009, Page(s):1428 - 1440
Cited by:  Papers (27)
| | PDF (362 KB) | HTML

This paper describes a decentralized H infin filter design for discrete-time interconnected fuzzy systems based on piecewise-quadratic Lyapunov functions. The systems consist of J discrete-time interconnected Takagi-Sugeno (T-S) fuzzy subsystems, and a decentralized H infin filter is designed for each subsystem. It is shown that the stability of the overa... View full abstract»

• Relaxed ${cal H}_{infty }$ Stabilization Conditions for Discrete-Time Fuzzy Systems With Interval Time-Varying Delays

Publication Year: 2009, Page(s):1441 - 1449
Cited by:  Papers (6)
| | PDF (233 KB) | HTML

To derive less-conservative delay- and range-dependent H infin stabilization conditions for discrete-time Takagi-Sugeno (T-S) fuzzy systems with interval time-varying delays, the use of a fuzzy-weighting-dependent Lyapunov-Krasovskii functional (FWLKF), in which all variables are set to be affinely or quadratically dependent on fuzzy weighting functions, is proposed. Subsequently... View full abstract»

• On Stability and Stabilization of T–S Fuzzy Time-Delayed Systems

Publication Year: 2009, Page(s):1450 - 1455
Cited by:  Papers (27)
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In this paper, the stability analysis and control design of Takagi-Sugeno (TS) fuzzy systems subject to uncertain time-delay are addressed. The proposed approach is based on linear matrix inequalities and the Lyapunov-Krasovskii theory, where a new fuzzy weighting-dependent Lyapunov-Krasovskii functional is introduced. By employing the Gu discretization technique and strategies to add slack matrix... View full abstract»

• Are More Features Better? A Response to Attributes Reduction Using Fuzzy Rough Sets

Publication Year: 2009, Page(s):1456 - 1458
Cited by:  Papers (18)
| | PDF (60 KB) | HTML

A recent TRANSACTIONS ON FUZZY SYSTEMS paper proposing a new fuzzy-rough feature selector (FRFS) has claimed that the more attributes remain in datasets, the better the approximations and hence resulting models. [Tsang , IEEE Trans. Fuzzy Syst. , vol. 16, no. 5, pp. 1130-1141]. This claim has been used as a primary criticism of the original FRFS method [Jensen and Shen, IEEE Trans. Fuzzy... View full abstract»

• 2009 Index IEEE Transactions on Fuzzy Systems Vol. 17

Publication Year: 2009, Page(s):1461 - 1478
| PDF (204 KB)

Publication Year: 2009, Page(s):1459 - 1460
| PDF (1065 KB)
• IEEE Computational Intelligence Society Information

Publication Year: 2009, Page(s): C3
| PDF (37 KB)
• IEEE Transactions on Fuzzy Systems Information for authors

Publication Year: 2009, 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