In this paper, evolution strategy is applied in order to improve the time series prediction accuracy of a Sugeno and Takagi type fuzzy inference system FIS. The presented approach...
One of the main obstacles to the widespread use of artijcial neural networks is the difJiculty of adequately define valuesfor their free parameters. This article discusses how Rad...
Estefane G. M. de Lacerda, Teresa Bernarda Ludermi...
The main purpose of this paper is to compare the support vector machine (SVM) developed by Vapnik with other techniques such as Backpropagation and Radial Basis Function (RBF) Net...
This paper is focused on determining the parameters of radial basis function neural networks (number of neurons, and their respective centers and radii) automatically. While this ...
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Wavelet neural networks (WNN) have recently attracted great interest, because of their advantages over radial basis function networks (RBFN) as they are universal approximators bu...
Even though numerous techniques for face recognition have been explored over the years, most research has primarily focussed on identification from full frontal/profile facial ima...
Srinivas Gutta, Vasanth Philomin, Miroslav Trajkov...
Abstract. An orthogonal forward selection (OFS) algorithm based on the leaveone-out (LOO) criterion is proposed for the construction of radial basis function (RBF) networks with tu...
In this paper, we propose a new algorithm for the fundamental problem of reconstructing surfaces from a large set of unorganized 3D data points. The local shapes of the surface ar...
— Recognition of digital signal type is an important topic for various applications. In this paper a method is presented that identifies different types of digital signals. This ...