<![CDATA[ IEEE Transactions on Fuzzy Systems - new TOC ]]>
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TOC Alert for Publication# 91 2017July 27<![CDATA[Table of Contents]]>253C1C441<![CDATA[IEEE Transactions on Fuzzy Systems]]>253C2C264<![CDATA[A Profit Maximizing Solid Transportation Model Under a Rough Interval Approach]]>253485498467<![CDATA[Design of State Feedback Adaptive Fuzzy Controllers for Second-Order Systems Using a Frequency Stability Criterion]]>253499510950<![CDATA[Dynamic Output-Feedback Dissipative Control for T–S Fuzzy Systems With Time-Varying Input Delay and Output Constraints]]>2535115262812<![CDATA[Adaptive Predefined Performance Control for MIMO Systems With Unknown Direction via Generalized Fuzzy Hyperbolic Model]]>2535275421413<![CDATA[Revisiting Fuzzy Set and Fuzzy Arithmetic Operators and Constructing New Operators in the Land of Probabilistic Linguistic Computing]]>253543555324<![CDATA[Asymptotic Fuzzy Tracking Control for a Class of Stochastic Strict-Feedback Systems]]>2535565681055<![CDATA[Approaches to T–S Fuzzy-Affine-Model-Based Reliable Output Feedback Control for Nonlinear Itô Stochastic Systems]]>∞ static output feedback (SOF) controller synthesis for continuous-time nonlinear stochastic systems with actuator faults. The nonlinear stochastic plant is expressed by an Itô-type Takagi-Sugeno fuzzy-affine model with parametric uncertainties, and a Markov process is employed to model the occurrence of actuator fault. The purpose is to design an admissible piecewise SOF controller, such that the resulting closed-loop system is stochastically stable with a prescribed disturbance attenuation level in an sense. Specifically, based on a Markovian Lyapunov function combined with Itô differential formula, S-procedure, and some matrix inequality convexification procedures, two new approaches to the reliable SOF controller analysis and synthesis are proposed for the underlying stochastic fuzzy-affine systems. It is shown that the existence of desired reliable controllers is fully characterized in terms of strict linear matrix inequalities. Finally, simulation examples are presented to illustrate the effectiveness and advantages of the developed methods.]]>253569583669<![CDATA[Pixel Modeling Using Histograms Based on Fuzzy Partitions for Dynamic Background Subtraction]]>253584593625<![CDATA[Varying Spread Fuzzy Regression for Affective Quality Estimation]]>2535946132074<![CDATA[Ranking of Multidimensional Uncertain Information Based on Metrics on the Fuzzy Ellipsoid Number Space]]>p are the most common metrics. However, due to the complexity of the level sets of usual n-dimensional fuzzy numbers, the two kinds of metrics not only have a tendency to be rougher, but also are difficult to give concrete expression formulas (this affects their theory and application research). In this paper, some new metrics on fuzzy ellipsoid number space are introduced, which not only can better reveal the difference between two different fuzzy ellipsoid numbers, but also have concrete expression formulas (expressed with the level set functions of fuzzy ellipsoid numbers). And the properties of the new introduced metrics and the relationships between the new metrics and the usual metrics (D and ρ_{p}) are studied, and some results are obtained. Then, we give the concept of supremum (infimum) of bounded subsets of fuzzy ellipsoid number space, and obtain its concrete calculation formula. And then, by using the obtained results, we propose a method to rank multidimensional uncertain information, and give a practical example to show the application and the rationality of the proposed techniques.]]>253614626460<![CDATA[The Spatial Disaggregation Problem: Simulating Reasoning Using a Fuzzy Inference System]]>253627641658<![CDATA[Adaptive Fuzzy Backstepping Tracking Control for Strict-Feedback Systems With Input Delay]]>2536426521140<![CDATA[Dynamic Output Feedback-Predictive Control of a Takagi–Sugeno Model With Bounded Disturbance]]>253653667695<![CDATA[Command-Filtered-Based Fuzzy Adaptive Control Design for MIMO-Switched Nonstrict-Feedback Nonlinear Systems]]>253668681849<![CDATA[Type-2 Fuzzy Alpha-Cuts]]>253682692508<![CDATA[A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems]]>2536937061306<![CDATA[LMI-Based Stability Analysis for Piecewise Multi-affine Systems]]>2537077141173<![CDATA[An Extended Type-Reduction Method for General Type-2 Fuzzy Sets]]>253715724656<![CDATA[Critique of “A New Look at Type-2 Fuzzy Sets and Type-2 Fuzzy Logic Systems”]]>253725727198<![CDATA[Special issue on visualization and visual analytics for multimedia]]>253728728370<![CDATA[IEEE Computational Intelligence Society]]>253C3C358