# IEEE Transactions on Fuzzy Systems

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• ### Dynamic Fuzzy Rule Interpolation and Its Application to Intrusion Detection

Publication Year: 2018, Page(s):1878 - 1892
Cited by:  Papers (3)
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Fuzzy rule interpolation (FRI) offers an effective approach for making inference possible in sparse rule-based systems (and also for reducing the complexity of fuzzy models). However, requirements of fuzzy systems may change over time and hence, the use of a static rule base may affect the accuracy of FRI applications. Fortunately, an FRI system in action will produce interpolated rules in abundan... View full abstract»

• ### A Hierarchical Fused Fuzzy Deep Neural Network for Data Classification

Publication Year: 2017, Page(s):1006 - 1012
Cited by:  Papers (9)
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Deep learning (DL) is an emerging and powerful paradigm that allows large-scale task-driven feature learning from big data. However, typical DL is a fully deterministic model that sheds no light on data uncertainty reductions. In this paper, we show how to introduce the concepts of fuzzy learning into DL to overcome the shortcomings of fixed representation. The bulk of the proposed fuzzy system is... View full abstract»

• ### Significantly Fast and Robust Fuzzy C-Means Clustering Algorithm Based on Morphological Reconstruction and Membership Filtering

Publication Year: 2018, Page(s):3027 - 3041
Cited by:  Papers (1)
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As fuzzy c-means clustering (FCM) algorithm is sensitive to noise, local spatial information is often introduced to an objective function to improve the robustness of the FCM algorithm for image segmentation. However, the introduction of local spatial information often leads to a high computational complexity, arising out of an iterative calculation of the distance between pixels within local spat... View full abstract»

• ### Dissipativity-Based Fuzzy Integral Sliding Mode Control of Continuous-Time T-S Fuzzy Systems

Publication Year: 2018, Page(s):1164 - 1176
Cited by:  Papers (29)
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This paper is concerned with dissipativity-based fuzzy integral sliding mode control (FISMC) of continuous-time Takagi-Sugeno (T-S) fuzzy systems with matched/unmatched uncertainties and external disturbance. To better accommodate the characteristics of T-S fuzzy models, an appropriate integral-type fuzzy switching surface is put forward by taking the state-dependent input matrix into account, whi... View full abstract»

• ### Fuzzy Rule Based Interpolative Reasoning Supported by Attribute Ranking

Publication Year: 2018, Page(s):2758 - 2773
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Using fuzzy rule interpolation (FRI) interpolative reasoning can be effectively performed with a sparse rule base where a given system observation does not match any fuzzy rules. While offering a potentially powerful inference mechanism, in the current literature, typical representation of fuzzy rules in FRI assumes that all attributes in the rules are of equal significance in deriving the consequ... View full abstract»

• ### Adaptive Sliding Mode Control for Takagi–Sugeno Fuzzy Systems and Its Applications

Publication Year: 2018, Page(s):531 - 542
Cited by:  Papers (12)
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This paper investigates the problem of adaptive integral sliding mode control for general Takagi-Sugeno fuzzy systems with matched uncertainties and its applications. Different control input matrices are allowed in fuzzy systems. The matched uncertainty is modeled in a unified form, which can be handled by the adaptive methodology. A fuzzy integral-type sliding surface is utilized and the paramete... View full abstract»

• ### Adaptive Fuzzy Output Feedback Control for a Class of Nonlinear Systems With Full State Constraints

Publication Year: 2018, Page(s):2607 - 2617
Cited by:  Papers (9)
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In the paper, the adaptive observer and controller designs based fuzzy approximation are studied for a class of uncertain nonlinear systems in strict feedback. The main properties of the considered systems are that all the state variables are not available for measurement and at the same time, they are required to limit in each constraint set. Due to the properties of systems, it will be a difficu... View full abstract»

• ### A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

Publication Year: 2006, Page(s):676 - 697
Cited by:  Papers (1004)
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Fuzzy logic control was originally introduced and developed as a model free control design approach. However, it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications. In the past ten years or so, prevailing research efforts on fuzzy logic control have been devoted to model-based fuzzy control s... View full abstract»

• ### Adaptive Fuzzy Fault-Tolerant Control for Uncertain Nonlinear Switched Stochastic Systems with Time-Varying Output Constraints

Publication Year: 2018, Page(s):2487 - 2498
Cited by:  Papers (1)
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Adaptive fuzzy fault-tolerant control problem for a class of uncertain switched stochastic nonlinear systems with time-varying asymmetric output constraints is addressed in this study. Under the action of well-designed asymmetric nonlinear mapping, fuzzy control technology, and backstepping recursive design scheme; the actuator faults of both loss of effectiveness and lock-in-place are considered ... View full abstract»

• ### A possibilistic fuzzy c-means clustering algorithm

Publication Year: 2005, Page(s):517 - 530
Cited by:  Papers (529)
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In 1997, we proposed the fuzzy-possibilistic c-means (FPCM) model and algorithm that generated both membership and typicality values when clustering unlabeled data. FPCM constrains the typicality values so that the sum over all data points of typicalities to a cluster is one. The row sum constraint produces unrealistic typicality values for large data sets. In this paper, we propose a new model ca... View full abstract»

• ### Fuzzy Restricted Boltzmann Machine for the Enhancement of Deep Learning

Publication Year: 2015, Page(s):2163 - 2173
Cited by:  Papers (55)
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In recent years, deep learning caves out a research wave in machine learning. With outstanding performance, more and more applications of deep learning in pattern recognition, image recognition, speech recognition, and video processing have been developed. Restricted Boltzmann machine (RBM) plays an important role in current deep learning techniques, as most of existing deep networks are based on ... View full abstract»

• ### Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence

Publication Year: 2018, Page(s):1704 - 1718
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A promising research area in the field of group decision making (GDM) is the study of interpersonal influence and its impact on the evolution of experts' opinions. In conventional GDM models, a group of experts express their individual preferences on a finite set of alternatives, then preferences are aggregated and the best alternative, satisfying the majority of experts, is selected. Nevertheless... View full abstract»

• ### Observer-Based Fuzzy Integral Sliding Mode Control For Nonlinear Descriptor Systems

Publication Year: 2018, Page(s):2818 - 2832
Cited by:  Papers (2)
| | PDF (770 KB) | HTML

This paper investigates observer-based stabilization for nonlinear descriptor systems using a fuzzy integral sliding mode control approach. Observer-based integral sliding mode control strategies for the Takagi-Sugeno (T-S) fuzzy descriptor systems are developed. A two-step design approach is first developed to obtain the observer gains and coefficients in the switching function using linear matri... View full abstract»

• ### Fuzzy Superpixels for Polarimetric SAR Images Classification

Publication Year: 2018, Page(s):2846 - 2860
Cited by:  Papers (1)
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Superpixels technique has drawn much attention in computer vision applications. Each superpixels algorithm has its own advantages. Selecting a more appropriate superpixels algorithm for a specific application can improve the performance of the application. In the last few years, superpixels are widely used in polarimetric synthetic aperture radar (PolSAR) image classification. However, no superpix... View full abstract»

• ### An Asynchronous Operation Approach to Event-Triggered Control for Fuzzy Markovian Jump Systems With General Switching Policies

Publication Year: 2018, Page(s):6 - 18
Cited by:  Papers (46)
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This paper investigates the problem of event-triggered control for a class of fuzzy Markov jump systems with general switching policies. A novel event-triggered scheme is proposed to improve the transmission efficiency at each sampling instance. Each transition rate allows to be unknown, known, or only its uncertain domains value is known. With the help of a tailored technique to bind the uncertai... View full abstract»

• ### Two-Stage Learning Based Fuzzy Cognitive Maps Reduction Approach

Publication Year: 2018, Page(s):2938 - 2952
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In this study, a new two-stage learning based reduction approach for fuzzy cognitive maps (FCM) is introduced in order to reduce the number of concepts. FCM is a graphical modeling technique that follows a reasoning approach similar to the human reasoning and the decision-making process. The FCM model incorporates the available knowledge and expertise in the form of concepts and in the direction a... View full abstract»

• ### Fuzzy Bag-of-Words Model for Document Representation

Publication Year: 2018, Page(s):794 - 804
Cited by:  Papers (2)
| | PDF (491 KB) | HTML

One key issue in text mining and natural language processing is how to effectively represent documents using numerical vectors. One classical model is the Bag-of-Words (BoW). In a BoW-based vector representation of a document, each element denotes the normalized number of occurrence of a basis term in the document. To count the number of occurrence of a basis term, BoW conducts exact word matching... View full abstract»

• ### Soft and Declarative Fishing of Information in Big Data Lake

Publication Year: 2018, Page(s):2732 - 2747
Cited by:  Papers (4)
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In recent years, many fields that experience a sudden proliferation of data, which increases the volume of data that must be processed and the variety of formats the data is stored in have been identified. This causes pressure on existing compute infrastructures and data analysis methods, as more and more data are considered as a useful source of information for making critical decisions in partic... View full abstract»

• ### Event-Based Reliable Dissipative Filtering for T–S Fuzzy Systems With Asynchronous Constraints

Publication Year: 2018, Page(s):2089 - 2098
Cited by:  Papers (7)
| | PDF (558 KB) | HTML

In this paper, event-triggered reliable dissipative filtering is investigated for a class of Takagi-Sugeno (T-S) fuzzy systems. First, a reliable event-triggered communication scheme is introduced to release sampled measurement outputs only if the variation of the sampled vector exceeds a prescribed threshold condition. Second, an asynchronous premise reconstruct method for T-S fuzzy systems is pr... View full abstract»

• ### Stabilization of Fuzzy Memristive Neural Networks With Mixed Time Delays

Publication Year: 2018, Page(s):2591 - 2606
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In this paper, stabilization for a class of Takagi-Sugeno (T-S) fuzzy memristive neural networks (FMNNs) with mixed time delays is investigated. By virtue of theories of differential equations with discontinuous right-hand sides, inequality techniques, and the comparison method, an algebraic criterion is derived to stabilize the addressed FMNNs with bounded discrete and distributed time delays via... View full abstract»

• ### On Distributed Fuzzy Decision Trees for Big Data

Publication Year: 2018, Page(s):174 - 192
Cited by:  Papers (12)
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Fuzzy decision trees (FDTs) have shown to be an effective solution in the framework of fuzzy classification. The approaches proposed so far to FDT learning, however, have generally neglected time and space requirements. In this paper, we propose a distributed FDT learning scheme shaped according to the MapReduce programming model for generating both binary and multiway FDTs from big data. The sche... View full abstract»

• ### A New Approach to Stability and Stabilization Analysis for Continuous-Time Takagi–Sugeno Fuzzy Systems With Time Delay

Publication Year: 2018, Page(s):2460 - 2465
Cited by:  Papers (1)
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Till now, there are lots of stability and stabilization results about Takagi-Sugeno (T-S) fuzzy systems with time delay, but most of them are independent of the analysis of membership functions. Since the membership functions are an essential component to make a fuzzy system different from others, the conditions without its information are conservative. In this brief paper, a new Lyapunov-Krasovsk... View full abstract»

• ### Observer-Based Composite Adaptive Fuzzy Control for Nonstrict-Feedback Systems With Actuator Failures

Publication Year: 2018, Page(s):2336 - 2347
Cited by:  Papers (10)
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This paper studies the observer-based adaptive fuzzy tracking control problem for a general class of multi-input-single-output nonstrict-feedback systems subject to unmeasured states and actuator failures. For actuator failures, both cases of lock-in-place and loss of effectiveness are synchronously considered. To handle the unknown nonlinear functions, fuzzy logic systems are employed. By constru... View full abstract»

• ### Consensus Building for the Heterogeneous Large-Scale GDM With the Individual Concerns and Satisfactions

Publication Year: 2018, Page(s):884 - 898
Cited by:  Papers (2)
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Nowadays, societal and technological trends demand the management of large scale of decision makers in group decision-making (GDM) contexts. In a large-scale GDM, decision makers often have individual concerns and satisfactions, and also they will use heterogeneous preference representation structures to express their preferences. Meanwhile, it is difficult to set the numerical consensus threshold... View full abstract»

• ### Finite-Time Event-Triggered $\mathcal{H}_{\infty }$ Control for T–S Fuzzy Markov Jump Systems

Publication Year: 2018, Page(s):3122 - 3135
Cited by:  Papers (2)
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This paper investigates the finite-time event-triggered 'I-1 control problem for Takagi-Sugeno Markov jump fuzzy systems. Because of the sampling behaviors and the effect of network environment, the premise variables considered in this paper are subject to asynchronous constraints. The aim of this paper is to synthesize a controller via an event-triggered communication scheme such that not only th... View full abstract»

• ### Event-Triggered Predictive Control for Networked Nonlinear Systems With Imperfect Premise Matching

Publication Year: 2018, Page(s):2797 - 2806
Cited by:  Papers (2)
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This paper investigates the event-triggered predictive control problem for networked nonlinear systems with imperfect premise matching. First, a model of networked nonlinear system is well constructed, which has integrated the event-triggered communication scheme (ETCS) and the predictive control together, in which, an ETCS is introduced to alleviate the communication burden by reducing the number... View full abstract»

• ### Optimized Multi-Agent Formation Control Based on an Identifier–Actor–Critic Reinforcement Learning Algorithm

Publication Year: 2018, Page(s):2719 - 2731
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The paper proposes an optimized leader-follower formation control for the multi-agent systems with unknown nonlinear dynamics. Usually, optimal control is designed based on the solution of the Hamilton-Jacobi-Bellman equation, but it is very difficult to solve the equation because of the unknown dynamic and inherent nonlinearity. Specifically, to multi-agent systems, it will become more complicate... View full abstract»

• ### Global Asymptotic Model-Free Trajectory-Independent Tracking Control of an Uncertain Marine Vehicle: An Adaptive Universe-Based Fuzzy Control Approach

Publication Year: 2018, Page(s):1613 - 1625
Cited by:  Papers (9)
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Motivated by the challenging difficulty in tracking an uncertain marine vehicle (MV) with unknown dynamics and disturbances to any unmeasurable/unknown trajectory, which is unresolved, an adaptive universe-based fuzzy control (AUFC) scheme with retractable fuzzy partitioning (RFP) in global universe of discourse (UoD) is created to achieve global asymptotic model-free trajectory-independent tracki... View full abstract»

• ### Observer-Based Adaptive Fuzzy Decentralized Optimal Control Design for Strict-Feedback Nonlinear Large-Scale Systems

Publication Year: 2018, Page(s):569 - 584
Cited by:  Papers (5)
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In this paper, the problem of adaptive fuzzy decentralized optimal control is investigated for a class of nonlinear large-scale systems in strict-feedback form. The considered nonlinear large-scale systems contain the unknown nonlinear functions and unmeasured states. By utilizing the fuzzy logic systems to approximate the unknown nonlinear functions and cost functions, a fuzzy state observer is e... View full abstract»

• ### Observer-Based Adaptive Decentralized Fuzzy Fault-Tolerant Control of Nonlinear Large-Scale Systems With Actuator Failures

Publication Year: 2014, Page(s):1 - 15
Cited by:  Papers (273)
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This paper investigates the adaptive fuzzy decentralized fault-tolerant control (FTC) problem for a class of nonlinear large-scale systems in strict-feedback form. The considered nonlinear system contains the unknown nonlinear functions, i.e., unmeasured states and actuator faults, which are modeled as both loss of effectiveness and lock-in-place. With the help of fuzzy logic systems to approximat... View full abstract»

• ### Robust Sliding Mode Control for T-S Fuzzy Systems via Quantized State Feedback

Publication Year: 2018, Page(s):2261 - 2272
Cited by:  Papers (1)
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This paper is concerned with the robust sliding mode control (SMC) problem for a class of T-S fuzzy systems subject to both matched and mismatched uncertainties. Different from the conventional T-S fuzzy SMC design approach, the quantized states rather than states themselves, are utilized for the control design. By the combination of the proposed zooming-out/zooming-in adjustment policy of the qua... View full abstract»

• ### Law of Large Numbers for Uncertain Random Variables

Publication Year: 2016, Page(s):615 - 621
Cited by:  Papers (26)
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The law of large numbers in probability theory states that the average of random variables converges to its expected value in some sense under some conditions. Sometimes, random factors and human uncertainty exist simultaneously in complex systems, and a concept of uncertain random variable has been proposed to study this type of complex systems. This paper aims to provide a law of large numbers f... View full abstract»

• ### Finite-Time Adaptive Fuzzy Tracking Control Design for Nonlinear Systems

Publication Year: 2018, Page(s):1207 - 1216
Cited by:  Papers (1)
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This paper addresses the finite-time tracking problem of nonlinear pure-feedback systems. Unlike the literature on traditional finite-time stabilization, in this paper the nonlinear system functions, including the bounding functions, are all totally unknown. Fuzzy logic systems are used to model those unknown functions. To present a finite-time control strategy, a criterion of semiglobal practical... View full abstract»

• ### Adaptive Fuzzy Robust Fault-Tolerant Optimal Control for Nonlinear Large-Scale Systems

Publication Year: 2018, Page(s):2899 - 2914
Cited by:  Papers (1)
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The problem of adaptive fuzzy decentralized fault-tolerant optimal control is investigated for nonlinear large-scale systems with actuator faults in this paper. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions and learn cost functions. Filtered signals are adopted to circumvent the problems of an algebraic loop on designing the decentralized controllers. Based on the... View full abstract»

• ### Spatially Piecewise Fuzzy Control Design for Sampled-Data Exponential Stabilization of Semilinear Parabolic PDE Systems

Publication Year: 2018, Page(s):2967 - 2980
Cited by:  Papers (2)
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This paper employs a Takagi-Sugeno (T-S) fuzzy partial differential equation (PDE) model to solve the problem of sampled-data exponential stabilization in the sense of spatial ∥·∥∞for a class of nonlinear parabolic distributed parameter systems (DPSs), where only a few actuators and sensors are discretely distributed in space. Initially, a T-S fuzzy PDE model is assumed to be derived by... View full abstract»

• ### Adaptive Fuzzy Sliding Mode Control for Network-Based Nonlinear Systems With Actuator Failures

Publication Year: 2018, Page(s):1311 - 1323
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This paper investigates the robust control problem of nonlinear systems with unknown time-varying actuator faults over digital communication networks. In the study, a new adaptive sliding mode control (SMC) scheme is developed for the investigated nonlinear systems, where the unknown nonlinearity is approximated via the adaptive fuzzy mechanism in the presence of signal quantization. The proposed ... View full abstract»

• ### Three-Layer Weighted Fuzzy Support Vector Regression for Emotional Intention Understanding in Human–Robot Interaction

Publication Year: 2018, Page(s):2524 - 2538
Cited by:  Papers (2)
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A three-layer weighted fuzzy support vector regression (TLWFSVR) model is proposed for understanding human intention, and it is based on the emotion-identification information in human-robot interaction. The TLWFSVR model consists of three layers, including adjusted weighted kernel fuzzy c-means for data clustering, fuzzy support vector regressions (FSVR) for information understanding, and weighte... View full abstract»

• ### Optimal Guaranteed Cost Sliding-Mode Control of Interval Type-2 Fuzzy Time-Delay Systems

Publication Year: 2018, Page(s):246 - 257
Cited by:  Papers (20)
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This paper is concerned with the optimal guaranteed cost sliding-mode control problem for interval type-2 (IT2) Takagi-Sugeno fuzzy systems with time-varying delays and exogenous disturbances. In the presence of the uncertain parameters hidden in membership functions, an adaptive method is presented to handle the time-varying weight coefficients reflecting the change of the uncertain parameters. A... View full abstract»

• ### Decentralized Event-Triggered Control for Large-Scale Networked Fuzzy Systems

Publication Year: 2018, Page(s):29 - 45
Cited by:  Papers (9)
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This paper addresses event-triggered data transmission in a class of large-scale networked nonlinear systems with transmission delays and nonlinear interconnections. Each nonlinear subsystem in the considered large-scale system is represented by a Takagi-Sugeno model, and exchanges its information through a digital channel. We propose an event-triggering mechanism, which determines when the premis... View full abstract»

• ### Fault Estimation and Fault-Tolerant Control for Switched Fuzzy Stochastic Systems

Publication Year: 2018, Page(s):2993 - 3003
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This paper addresses the problems of fault estimation and fault-tolerant control for switched fuzzy stochastic systems with actuator fault and sensor fault. A novel observer is proposed to estimate the system states, actuator, and sensor faults, simultaneously. The proposed observer can be treated as an extension of the traditional proportional-integral observer. The estimation information is util... View full abstract»

• ### Further Results on Stabilization of Chaotic Systems Based on Fuzzy Memory Sampled-Data Control

Publication Year: 2018, Page(s):1040 - 1045
Cited by:  Papers (8)
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This note investigates sampled-data control for chaotic systems. A memory sampled-data control scheme that involves a constant signal transmission delay is employed for the first time to tackle the stabilization problem for Takagi-Sugeno fuzzy systems. The advantage of the constructed Lyapunov functional lies in the fact that it is neither necessarily positive on sampling intervals nor necessarily... View full abstract»

• ### A Feature-Reduction Fuzzy Clustering Algorithm Based on Feature-Weighted Entropy

Publication Year: 2018, Page(s):817 - 835
Cited by:  Papers (5)
| | PDF (1666 KB) | HTML

Fuzzy clustering algorithms generally treat data points with feature components under equal importance. However, there are various datasets with irrelevant features involved in clustering process that may cause bad performance for fuzzy clustering algorithms. That is, different feature components should take different importance. In this paper, we present a novel method for improving fuzzy cluster... View full abstract»

• ### Hesitant Fuzzy Linguistic Term Sets for Decision Making

Publication Year: 2012, Page(s):109 - 119
Cited by:  Papers (625)
| | PDF (417 KB) | HTML

Dealing with uncertainty is always a challenging problem, and different tools have been proposed to deal with it. Recently, a new model that is based on hesitant fuzzy sets has been presented to manage situations in which experts hesitate between several values to assess an indicator, alternative, variable, etc. Hesitant fuzzy sets suit the modeling of quantitative settings; however, similar situa... View full abstract»

• ### Interval Type-2 Fuzzy Logic Modeling and Control of a Mobile Two-Wheeled Inverted Pendulum

Publication Year: 2018, Page(s):2030 - 2038
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This paper presents an integrated interval type-2 fuzzy logic approach that simultaneously models and controls an underactuated mobile two-wheeled inverted pendulum (MTWIP), which suffers from modeling uncertainties and external disturbances. The control objective is to attain the desired position and direction while keeping the MTWIP balanced. It is achieved by integrating four interval type-2 fu... View full abstract»

• ### Type-2 fuzzy sets made simple

Publication Year: 2002, Page(s):117 - 127
Cited by:  Papers (1256)
| | PDF (429 KB) | HTML

Type-2 fuzzy sets let us model and minimize the effects of uncertainties in rule-base fuzzy logic systems. However, they are difficult to understand for a variety of reasons which we enunciate. In this paper, we strive to overcome the difficulties by: (1) establishing a small set of terms that let us easily communicate about type-2 fuzzy sets and also let us define such sets very precisely, (2) pr... View full abstract»

• ### Interval Type-2 Fuzzy Logic Systems Made Simple

Publication Year: 2006, Page(s):808 - 821
Cited by:  Papers (863)
| | PDF (899 KB) | HTML

To date, because of the computational complexity of using a general type-2 fuzzy set (T2 FS) in a T2 fuzzy logic system (FLS), most people only use an interval T2 FS, the result being an interval T2 FLS (IT2 FLS). Unfortunately, there is a heavy educational burden even to using an IT2 FLS. This burden has to do with first having to learn general T2 FS mathematics, and then specializing it to an IT... View full abstract»

• ### Adaptive Fuzzy Backstepping Tracking Control for Strict-Feedback Systems With Input Delay

Publication Year: 2017, Page(s):642 - 652
Cited by:  Papers (70)
| | PDF (1140 KB) | HTML

This paper investigates the problem of adaptive fuzzy tracking control for nonlinear strict-feedback systems with input delay and output constraint. Input delay is handled based on the information of Pade approximation and output constraint problem is solved by barrier Lypaunov function. Some adaptive parameters of the controller need to be updated online through considering the norm of membership... View full abstract»

• ### Spatial Filtering for EEG-Based Regression Problems in Brain–Computer Interface (BCI)

Publication Year: 2018, Page(s):771 - 781
Cited by:  Papers (3)
| | PDF (1419 KB) | HTML

Electroencephalogram (EEG) signals are frequently used in brain-computer interfaces (BC!s), but they are easily contaminated by artifacts and noise, so preprocessing must be done before they are fed into a machine learning algorithm for classification or regression. Spatial filters have been widely used to increase the signal-to-noise ratio of EEG for BC! classification problems, but their applica... View full abstract»

• ### Fuzzy Double C-Means Clustering Based on Sparse Self-Representation

Publication Year: 2018, Page(s):612 - 626
Cited by:  Papers (2)
| | PDF (2646 KB) | HTML

This paper introduces the popular sparse representation method into the classical fuzzy c-means clustering algorithm, and presents a novel fuzzy clustering algorithm, called fuzzy double c-means based on sparse self-representation (FDCM_SSR). The major characteristic of FDCM_SSR is that it can simultaneously address two datasets with different dimensions, and has two kinds of corresponding cluster... View full abstract»

• ### Assessment of the Impact of Hydropower Stations on the Environment With a Hesitant Fuzzy Linguistic Hyperplane-Consistency Programming Method

Publication Year: 2018, Page(s):2981 - 2992
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To reduce water conservancy projects' negative effects on the ecological environment, in this paper, a method is proposed to assess the impact of hydropower stations on the environment in the processes of the flood discharge and energy dissipation. It utilizes the hesitant fuzzy linguistic information to describe the problem's uncertainty and fuzziness, portrays decision maker's satisfaction degre... View full abstract»

## Aims & Scope

The IEEE Transactions on Fuzzy Systems (TFS) is published monthly. 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