This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
In this paper we propose a radial basis function (RBF) neural network for nonlinear time-invariant channel equalizer. The RBF network model has a three-layer structure which is com...
In this paper we focus on an interpretation of Gaussian radial basis functions (GRBF) which motivates extensions and learning strategies. Specifically, we show that GRBF regressio...
This article presents a new system for automatically constructing and training radial basis function networks based on original evolutionary computing methods. This system, called...
Forecasting exchange rates is an important financial problem that is receiving increasing attention especially because of its difficulty and practical applications. This paper prop...