Clustering has been used in various fields, such as image processing, data mining, pattern recognition, and statistical analysis. Generally, clustering algorithms consider all variables equally relevant or not correlated. Nevertheless, the of samples multidimensional space can be geometrically complicated, e.g., clusters may exist different subsets features. In this regard, new soft subspace ha...

Auscultation is an important tool for diagnosing respiratory-related diseases. Unfortunately, the quality of auscultation limited by professional level doctor and environment auscultation. Some studies have focused on automated techniques. However, existing approaches suffer from two challenges: 1) models cannot learn data distributed among multiple hospitals 2) predictions are difficult to int...

This paper presents a regularized fuzzy c-means clustering method for brain tissue segmentation from magnetic resonance images. A regularizer of the total variation type is explored and a method to estimate the regularization parameter is proposed. 2007 Elsevier B.V. All rights reserved.

Estimation of distribution algorithm for optimization of neural networks for intrusion detection system p. 9 Neural network implementation in reprogrammable FPGA devices-an example for MLP p. 19 A new approach for finding an optimal solution and regularization by learning dynamic momentum p. 29 Domain dynamics in optimization tasks p. 37 Nonlinear function learning by the normalized radial basi...

Abstract — This paper is devoted to the mathematical analysis and the numerical solution of the problem of designing fuzzy controllers. We show that for a special class of controllers (socalled Sugeno controllers), the design problem is equivalent to a nonlinear least squares problem, which turns out to be ill-posed. Therefore we investigate the use of regularization methods in order to obtain ...

Against to the different regions of membership functions indicated image in the traditional image segmentation variational model, resulting segmentation is not clear, de-noising effect is not obvious problems, this paper proposes multi-target model for image segmentation and the splitting algorithm. The model uses a sparse regularization method to maintain the boundaries of segmented regions, t...

We introduce in this paper a new formulation of the regularized fuzzy C-means (FCM) algorithm which allows us to find automatically the actual number of clusters. The approach is based on the minimization of an objective function which mixes, via a particular parameter, a classical FCM term and a new entropy regularizer. The main contribution of the method is the introduction of a new exponenti...

The methods applied to regularization of the ill-posed problems can be classified under “direct” and “indirect” methods. Practice has shown that the effects of different regularization techniques on an ill-posed problem are not the same, and as such each ill-posed problem requires its own investigation in order to identify its most suitable regularization method. In the geoid computations witho...