We introduce a machine learning based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanosc...
Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo
This paper presents a segmentation-based handwriting recognizer and the performance that it achieves on the numerical fields extracted from a large single-writer historical collec...
Marius Bulacu, Axel Brink, Tijn van der Zant, Lamb...
Abstract. One of the main problems associated with arti cial neural networks online learning methods is the estimation of model order. In this paper, we report about a new approach...
Forecasting exchange rates is an important financial problem that is receiving increasing attention especially because of its difficulty and practical applications. This paper prop...
In this paper two areas of soft computing (fuzzy modeling and artificial neural networks) are discussed. Based on the fundamental mathematical similarity of fuzzy technique and ra...
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function netwo...
Usually time series prediction is done with regularly sampled data. In practice, however, the data available may be irregularly sampled. In this case the conventional prediction me...
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
This paper presents a new framework that integrates relevance feedback into region-based image retrieval (RBIR) systems based on radial basis function network (RBFN). A modified u...