In this paper we examine the use of neural networks as a tool for predicting the success of basketball teams in the National Basketball Association (NBA). Statistics for 620 NBA games were collected and used to train a variety of neural networks such as feed-forward, radial basis, probabilistic...

Learning algorithms based on the Fourier transform attempt to learn functions by approximating the largest coefficients of their Fourier representations. Nearly all previous work in Fourier-based learning has been in the theoretical realm, where properties of the transform have made it possible...

In this paper, a new algorithm for RBF centers initialization for functional approximation problems is proposed. The design of the algorithm is inspired in previous clustering algorithms but adding some features to adapt the algorithm to the characteristics of our problem. We compare the results...