IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)

There are many important issues that need to be resolved for identification of a fuzzy rule-based system using clustering. We address three such important issues: 1) deciding on the proper domain(s) of clustering; 2) deciding on the number of rules; and 3) getting an initial estimate of parameters of the fuzzy systems. We justify that one should start with separate clustering of X (input) and Y (o... View full abstract»

Presents an ellipsoidal calculus based solely on two basic operations: propagation and fusion. Propagation refers to the problem of obtaining an ellipsoid that must satisfy an affine relation with another ellipsoid, and fusion to that of computing the ellipsoid that tightly bounds the intersection of two given ellipsoids. These two operations supersede the Minkowski sum and difference, affine tran... View full abstract»

The basic principle used in the construction of nearest-neighbor models is discussed. The induced ordered weighted averaging (IOWA) operators are shown to provide a useful formal structure for building nearest-neighbor models. A methodology for learning IOWA operator nearest-neighbor models is described. Various types of nearest-neighbor rules are investigated, including those based on a linguisti... View full abstract»

The notion of the necessary criticality (both with respect to path and to activity) of a network with imprecisely defined (by means of intervals or fuzzy intervals) activity duration times is introduced and analyzed. It is shown, in the interval case, that both the problem of asserting whether a given path is necessarily critical and the problem of determining an arbitrary necessarily critical pat... View full abstract»

A novel adaptive fuzzy-neural sliding-mode controller with H∞ tracking performance for uncertain nonlinear systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors. Because of the advantages of fuzzy-neural systems, which can uniformly approximate nonlinear continuous functions to arbitrary accuracy, adaptive fuzzy-neural contr... View full abstract»

Presents a novel method which uses a special type of multi-scale isotropic band-pass filters to detect image landmark and corner features. This paper mainly contributes to the solutions of the following problems: (1) defining a general family of feature detectors under a unified framework that are able to enhance and detect the desired features; (2) explaining theoretically and experimentally why ... View full abstract»

This paper introduces a new learning methodology to quickly generate accurate and simple linguistic fuzzy models: the cooperative rules (COR) methodology. It acts on the consequents of the fuzzy rules to find those that are best cooperating. Instead of selecting the consequent with the highest performance in each fuzzy input subspace, as ad-hoc data-driven methods usually do, the COR methodology c... View full abstract»

In order to make it possible to effectively represent deterministic uncertainties and vagueness as well as the human subjective observation and judgement inherent to many real-world problems, especially those in biomedicine, we introduce, in this paper, fuzzy states and fuzzy events and generalize (crisp) discrete event systems (DES) to fuzzy DES. The largely graph-based current framework of the c... View full abstract»

This work improves recent results concerning the adaptive control of mobile robots via neural and wavelet networks, in the sense that the stability proof, based on the second method of Lyapunov, encompasses (1) unmodeled dynamics and disturbances in the robot model; (2) adaptation of all parameters in the wavelet networks; and (3) a flexible procedure for automatically adjusting the wavelet archit... View full abstract»

It has been observed that human limb motions are not very accurate, leading to the hypothesis that the human motor control system may have simplified motion commands at the expense of motion accuracy. Inspired by this hypothesis, we propose learning schemes that trade motion accuracy for motion command simplification. When the original complex motion commands capable of tracking motion accurately ... View full abstract»

In this paper, a learning-based feedforward term is developed to solve a general control problem in the presence of unknown nonlinear dynamics with a known period. Since the learning-based feedforward term is generated from a straightforward Lyapunov-like stability analysis, the control designer can utilize other Lyapunov-based design techniques to develop hybrid control schemes that utilize learn... View full abstract»

A framework for multi-user distributed virtual environments (DVEs) has been proposed. The proposed framework, incorporating two models (the functional model and the interconnection model), attempts to represent the common functionality, communication issues and requirements found in multi-user DVEs. The functional model concentrates on the DVE's functionality, while the interconnection model conce... View full abstract»

A computationally efficient artificial neural network (ANN) for the purpose of dynamic nonlinear system identification is proposed. The major drawback of feedforward neural networks, such as multilayer perceptrons (MLPs) trained with the backpropagation (BP) algorithm, is that they require a large amount of computation for learning. We propose a single-layer functional-link ANN (FLANN) in which th... View full abstract»

We present a simple modification of the iterative learning control algorithm of Arimoto et al. (1984) for the case where the inputs are bounded and time-rate-limited. The Jacobian error condition for monotonicity of input-error, rather than output-error, norms, is specified, the latter being insufficient to assure convergence, as proved herein. To the best of our knowledge, these facts have not be... View full abstract»