Title :
Correlation feedback resource allocation RBF
Author :
Anderle, Markus ; Kirby, Michael
Author_Institution :
Dept. of Math., Colorado State Univ., Fort Collins, CO, USA
Abstract :
A model validation test based on simple linear autocorrelation is proposed as an objective method to determine the optimal number of units in the hidden layer of a radial basis function network. The data to be fitted is assumed to consist of a signal with additive iid noise. A novel stopping criteria is introduced based on the statistics of the residuals rather than on ad hoc parameters. Consequently, this network is shown to neither overfit nor underfit the data. In addition, each new unit is adjusted to respond locally to the target data
Keywords :
correlation methods; feedback; noise; radial basis function networks; resource allocation; RBF neural networks; additive noise; autocorrelation; model validation test; radial basis function network; resource allocation; stopping criteria; Additive noise; Feedback; Least squares approximation; Mathematics; Nonhomogeneous media; Radial basis function networks; Radio access networks; Resource management; Statistics; Testing;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.938462
