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IEEE Transactions on Fuzzy Systems

Issue 2 • Date Apr 2000

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Displaying Results 1 - 9 of 9
  • Clustering algorithms based on volume criteria

    Publication Year: 2000, Page(s):228 - 236
    Cited by:  Papers (31)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (684 KB)

    Clustering algorithms such as the K-means algorithm and the fuzzy C-means algorithm are based on the minimization of the trace of the (fuzzy) within-fluster scatter matrix. In this paper, we explore the use of determinant (volume) criteria for clustering. We derive an algorithm called the minimum scatter volume (MSV) algorithm, that minimizes the scatter volume, and another algorithm called the mi... View full abstract»

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  • On connectionism, rule extraction, and brain-like learning

    Publication Year: 2000, Page(s):222 - 227
    Cited by:  Papers (19)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (72 KB)

    There is a growing body of work that shows that both fuzzy and symbolic rule systems can be implemented using neural networks. This body of work also shows that these fuzzy and symbolic rules can be retrieved from these networks, once they have been learned by procedures that generally fall under the category of rule extraction. The paper argues that the idea of rule extraction from a neural netwo... View full abstract»

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  • Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement

    Publication Year: 2000, Page(s):212 - 221
    Cited by:  Papers (222)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (240 KB)

    Fuzzy modeling of high-dimensional systems is a challenging topic. This paper proposes an effective approach to data-based fuzzy modeling of high-dimensional systems. An initial fuzzy rule system is generated based on the conclusion that optimal fuzzy rules cover extrema. Redundant rules are removed based on a fuzzy similarity measure. Then, the structure and parameters of the fuzzy system are opt... View full abstract»

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  • Adaptive control of robot manipulator using fuzzy compensator

    Publication Year: 2000, Page(s):186 - 199
    Cited by:  Papers (107)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (664 KB)

    This paper presents two kinds of adaptive control schemes for robot manipulator which has the parametric uncertainties. In order to compensate these uncertainties, we use the FLS (fuzzy logic system) that has the capability to approximate any nonlinear function over the compact input space. In the proposed control schemes, we need not derive the linear formulation of robot dynamic equation and tun... View full abstract»

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  • Analysis and synthesis of nonlinear time-delay systems via fuzzy control approach

    Publication Year: 2000, Page(s):200 - 211
    Cited by:  Papers (476)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (704 KB)

    Takagi-Sugeno (TS) fuzzy models (1985, 1992) can provide an effective representation of complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear input/output (I/O) submodels. In this paper, the TS fuzzy model approach is extended to the stability analysis and control design for both continuous and discrete-time nonlinear systems with time delay. The TS fuzzy ... View full abstract»

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  • On multistage fuzzy neural network modeling

    Publication Year: 2000, Page(s):125 - 142
    Cited by:  Papers (70)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (572 KB)

    In the past couple of years, there has been increasing interest in the fusion of neural networks and fuzzy logic. Most of the existing fuzzy neural network (FNN) models have been proposed to implement different types of single-stage fuzzy reasoning mechanisms and inevitably they suffer from the dimensionality problem when dealing with complex real-world problems. To address the problem, FNN modeli... View full abstract»

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  • On aggregation operators for ordinal qualitative information

    Publication Year: 2000, Page(s):143 - 154
    Cited by:  Papers (49)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (552 KB)

    In many fuzzy systems applications, values to be aggregated are of a qualitative nature. In that case, if one wants to compute some type of average, the most common procedure is to perform a numerical interpretation of the values, and then apply one of the well-known (the most suitable) numerical aggregation operators. However, if one wants to stick to a purely qualitative setting, choices are red... View full abstract»

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  • A novel fuzzy logic system based on N-version programming

    Publication Year: 2000, Page(s):155 - 170
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (536 KB)

    For the consideration of different application systems, modeling the fuzzy logic rule, and deciding the shape of membership functions are very critical issues due to they play key roles in the design of fuzzy logic control system. This paper proposes a novel design methodology of fuzzy logic control system using the neural network and fault-tolerant approaches. The connectionist architecture with ... View full abstract»

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  • Optimal fuzzy controller design: local concept approach

    Publication Year: 2000, Page(s):171 - 185
    Cited by:  Papers (61)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (732 KB)

    In this paper, we present a global optimal and stable fuzzy controller design method for both continuous- and discrete-time fuzzy systems under both finite and infinite horizons. First, a sufficient condition is proposed which indicates that the global optimal effect can be achieved by the fuzzily combined local optimal controllers. Based on this sufficient condition, we derive a local concept app... View full abstract»

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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
Chin-Teng Lin
National Chiao-Tung University
Hsinchu 30010, Taiwan 
ctlin@mail.nctu.edu.tw
Phone: 886-3-5731753
Fax: 886-3-5727382