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IEEE Transactions on Fuzzy Systems

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Publication Year: 2010, Page(s): C1
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• IEEE Transactions on Fuzzy Systems publication information

Publication Year: 2010, Page(s): C2
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• Toward General Type-2 Fuzzy Logic Systems Based on zSlices

Publication Year: 2010, Page(s):637 - 660
Cited by:  Papers (165)
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Higher order fuzzy logic systems (FLSs), such as interval type-2 FLSs, have been shown to be very well suited to deal with the high levels of uncertainties present in the majority of real-world applications. General type-2 FLSs are expected to further extend this capability. However, the immense computational complexities associated with general type-2 FLSs have, until recently, prevented their ap... View full abstract»

• Robust $L_{bf 2}$-Gain Compensative Control for Direct-Adaptive Fuzzy-Control-System Design

Publication Year: 2010, Page(s):661 - 673
Cited by:  Papers (24)
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In this study, an effective and systematical robust approach for adaptive fuzzy-control-system design is proposed. In the design, a compensative-control law is proposed to provide the finite L2-gain property for direct-adaptive fuzzy-control systems to cope with possible external disturbances and approximation errors of the system. An integral term is further introduced into the ... View full abstract»

• Adaptive Backstepping Fuzzy Control for Nonlinearly Parameterized Systems With Periodic Disturbances

Publication Year: 2010, Page(s):674 - 685
Cited by:  Papers (121)
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A novel-function approximator is constructed by combining a fuzzy-logic system with a Fourier series expansion in order to model unknown periodically disturbed system functions. Then, an adaptive backstepping tracking-control scheme is developed, where the dynamic-surface-control approach is used to solve the problem of “explosion of complexity” in the backstepping design procedure, ... View full abstract»

• An Interval Type-2 Fuzzy-Neural Network With Support-Vector Regression for Noisy Regression Problems

Publication Year: 2010, Page(s):686 - 699
Cited by:  Papers (58)
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This paper proposes an interval type-2 fuzzy-neural network with support-vector regression (IT2FNN-SVR) for noisy regression problems. The antecedent part in each fuzzy rule of an IT2FNN-SVR uses interval type-2 fuzzy sets, and the consequent part is of the Takagi-Sugeno-Kang (TSK) type. The use of interval type-2 fuzzy sets helps improve the network's noise resistance. The network inputs may be n... View full abstract»

• Robust Adaptive Sliding-Mode Control for Fuzzy Systems With Mismatched Uncertainties

Publication Year: 2010, Page(s):700 - 711
Cited by:  Papers (124)
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This paper is devoted to design adaptive sliding-mode controllers for the Takagi-Sugeno (T--S) fuzzy system with mismatched uncertainties and exogenous disturbances. The uncertainties in state matrices are mismatched and norm-bounded, while the exogenous disturbances are assumed to be bounded with an unknown bound, which is estimated by a simple and effective adaptive approach. Both state- and sta... View full abstract»

• Robust $H_{infty }$ Fuzzy Output-Feedback Control With Multiple Probabilistic Delays and Multiple Missing Measurements

Publication Year: 2010, Page(s):712 - 725
Cited by:  Papers (139)
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In this paper, the robust H-control problem is investigated for a class of uncertain discrete-time fuzzy systems with both multiple probabilistic delays and multiple missing measurements. A sequence of random variables, all of which are mutually independent but obey the Bernoulli distribution, is introduced to account for the probabilistic communication delays. The measur... View full abstract»

• Robust Relief-Feature Weighting, Margin Maximization, and Fuzzy Optimization

Publication Year: 2010, Page(s):726 - 744
Cited by:  Papers (16)
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A latest advance in Relief-feature-weighting techniques is that the iterative procedure of Relief can be approximately expressed as a margin maximization problem, and therefore, its distinctive properties can be investigated with the help of optimization theory. Being motivated by this advance, the Relief-feature-weighting algorithm is investigated for the first time within a fuzzy-optimization fr... View full abstract»

• Fuzzy Data Standardization

Publication Year: 2010, Page(s):745 - 754
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Data standardization is a basic task in data analysis when several incommensurable criteria are involved. This paper discusses a data-standardization method for a set of fuzzy numbers that subtracts their minimum from the number to be standardized and divides the result by the difference between their maximum and minimum. Two approaches, i.e., membership grade and α-cut, are proposed, and a... View full abstract»

• An Evolving-Construction Scheme for Fuzzy Systems

Publication Year: 2010, Page(s):755 - 770
Cited by:  Papers (20)
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This paper proposes an evolving-construction scheme for fuzzy systems (ECSFS). ECSFS begins with a simple fuzzy system and evolves its structure by adding more fuzzy terms and rules to achieve a better accuracy in a "greedy'' way. An interesting feature of ECSFS is that it is able to automatically locate mathematically meaningful points, such as the extremum and inflexion points of the approximate... View full abstract»

• Relational Generalizations of Cluster Validity Indices

Publication Year: 2010, Page(s):771 - 786
Cited by:  Papers (18)
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Numerous computational schemes have arisen over the years that attempt to learn information about objects based upon the similarity or dissimilarity of one object to another. One such scheme, clustering, looks for self-similar groups of objects. To use clustering algorithms, an investigator must often have a priori knowledge of the number of clusters, i.e., c, to search for in the data. Mor... View full abstract»

• Variational Bayes for a Mixed Stochastic/Deterministic Fuzzy Filter

Publication Year: 2010, Page(s):787 - 801
Cited by:  Papers (7)
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This study, under the variational Bayes (VB) framework, infers the parameters of a Takagi-Sugeno fuzzy filter having deterministic antecedents and stochastic consequents. The aim of this study is to take advantages of the VB framework to design fuzzy-filtering algorithms, which include an automated regularization, incorporation of statistical noise models, and model-comparison capability. The VB m... View full abstract»

• Derivation and Analysis of the Analytical Structures of the Interval Type-2 Fuzzy-PI and PD Controllers

Publication Year: 2010, Page(s):802 - 814
Cited by:  Papers (62)
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Research results on type-2 (T2) fuzzy control have started to emerge in the literature over the past several years. None of these results, however, are concerned with the explicit input-output mathematical structure of a T2 fuzzy controller. As the literature on type-1 (T1) fuzzy control has demonstrated, revealing such structure information is important as it will deepen our precise understanding... View full abstract»

• Generalized Nonquadratic Stability of Continuous-Time Takagi–Sugeno Models

Publication Year: 2010, Page(s):815 - 822
Cited by:  Papers (96)
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This paper provides generalized nonquadratic stability conditions for continuous-time nonlinear models in the Takagi-Sugeno (TS) form obtained by sector-nonlinearity approach. Should global quadratic stability fail for a given nonlinear model, the proposed approach allows the obtaining of progressively better estimations of the stability domain via local asymptotic conditions in the form of linear... View full abstract»

• Fuzzy Compositional Modeling

Publication Year: 2010, Page(s):823 - 840
Cited by:  Papers (20)
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Automated modeling refers to automatic (re-)formulation of alternative system models that embody the simplification, abstraction, and approximation of knowledge and data for a given task. This technique is highly desirable for effective problem solving in many application domains. Over the past two decades, compositional modeling (CM) has established itself as a leading approach in automated model... View full abstract»

• Type-2 Fuzzy Sets as Functions on Spaces

Publication Year: 2010, Page(s):841 - 844
Cited by:  Papers (43)
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For many readers and potential authors, type-2 (T2) fuzzy sets might be more readily understood if expressed by the use of standard mathematical notation and terminology. This paper, therefore, translates constructs associated with T2 fuzzy sets to the language of functions on spaces. Such translations may encourage researchers in different disciplines to investigate T2 fuzzy sets, thereby potenti... View full abstract»

• IEEE Computational Intelligence Society Information

Publication Year: 2010, Page(s): C3
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• IEEE Transactions on Fuzzy Systems Information for authors

Publication Year: 2010, Page(s): C4
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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.

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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