Using radial basis function networks for function approximation tasks suffers from unavailable knowledge about an adequate network size. In this work, a measuring technique is proposed which can control the model complexity and is based on the correlation coefficient between two basis functions. Simulation results show good performance and, therefore, this technique can be integrated in the RBF...

Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization performance in detection and classification of VOC data. However, in many applications involving VOC data, it is not unusual for additional data, which may include new classes, to become available over time, which then req...

In this paper we introduce adaptive vision techniques used, for example, in video-conferencing applications. Radial Basis Function (RBF) networks have been trained for gesture-based communication with colour/motion cues to direct face detection and capture ‘attentional frames’. These focus the processing for Visually Mediated Interaction via an appearance-based approach with Gabor filter coeffi...

In this work several attemps are proposed for extracting the Jominy hardness pro les of steel directly from the steel chemical composition. It is essentially a black{box modelling problem: the neural approach seems powerful, especially compared with classical models commonly found in literature. Several network structures have been implemented, which all can be viewed under the uni cation parad...

A method for optimal adaptive setting of pulse-positionmodulation pulse detection thresholds, which minimizes the total probability of error for the dynamically fading optical free space channel, is presented. The threshold’s adaptive setting, in response to varying channel conditions, results in orders of magnitude improvement in probability of error, as compared to use of a fixed threshold. T...

This paper describes the International Institute of Information Technology of Hyderabad’s submission to the task Classification Of Spanish Election Tweets (COSET) as a part of IBEREVAL-2017[1]. The task is to classify Spanish election tweets into political, policy, personal, campaign and other issues. Our system uses Support Vector Machines with radial basis function kernel to classify tweets. ...

Very few studies involve how to construct the efficient RBFs by means of problem features. Recently the present author presented general solution RBF (GS-RBF) methodology to create operator-dependent RBFs successfully [1]. On the other hand, the normal radial basis function (RBF) is defined via Euclidean space distance function or the geodesic distance [2]. This purpose of this note is to redef...

In this paper, we discuss multiscale radial basis function collocation methods for solving certain elliptic partial differential equations on the unit sphere. The approximate solution is constructed in a multi-level fashion, each level using compactly supported radial basis functions of smaller scale on an increasingly fine mesh. Two variants of the collocation method are considered (sometimes ...

We propose a method of function approximation by radial basis function networks. We will demonstrate that this approximation method can be improved by a pre-treatment of data based on a linear model. This approximation method will be applied to option pricing. This choice justifies itself through the known nonlinear nature of the behavior of options price and through the effective contribution ...