• J. Beringer and E. Hüllermeier. Efficient instance based learning on data streams. Adaptive optimization of the number of clusters in fuzzy clustering. Fuzzy clustering of parallel data streams. Adaptive optimization of the number of clusters in fuzzy clustering.

Abstract. We present an error estimator based on firstand second-order derivatives recovery for finite element adaptive analysis. At first, we briefly discuss the abstract framework of the adopted error estimation techniques. Some possibilities of derivatives recovery are considered, including the proposal of a directional error estimator. Using the directional error estimator proposed, an adap...

We consider a wavelet thresholding approach to adaptive variance function estimation in heteroscedastic nonparametric regression. A data-driven estimator is constructed by applying wavelet thresholding to the squared first-order differences of the observations. We show that the variance function estimator is nearly optimally adaptive to the smoothness of both the mean and variance functions. Th...

The performances of two different estimators of a discriminant function of a statistical pattern recognizer are compared. One estimator is based on binary label values of the objects of the learning set (hard labels) and the other on continuous or multi-discrete label values in the interval [03] (fuzzy labels). By the latter estimator more detailed a priori knowledge of the contributing learnin...

In this paper we proposes a new control strategy for an interior permanent magnet synchronous generator-based(IPMSG) variable speed wind turbine. In this scheme, the requirement of the continuous rotor position is eliminated as all the calculations are done in the stator reference frame.. The direct control scheme with fuzzy logic controller (FLC) is simpler and can eliminate some of the drawba...

this paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. the uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. the contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...

In this paper, a new adaptive fuzzy reasoning method using compensatory fuzzy operators is proposed to make a fuzzy logic system more adaptive and more effective. Such a compensatory fuzzy logic system is proved to be a universal approximator. The compensatory neural fuzzy networks built by both control-oriented fuzzy neurons and decision-oriented fuzzy neurons cannot only adaptively adjust fuz...

Suppose we observe an ergodic Markov chain on the real line, with a parametric model for the autoregression function, i.e. the conditional mean of the transition distribution. If one speciies, in addition, a paramet-ric model for the conditional variance, one can deene a simple estimator for the parameter, the maximum quasi-likelihood estimator. It is robust against misspeciication of the condi...