Title :
RBF networks for density estimation
Author :
Sardo, Lucia ; Kittler, Josef
Author_Institution :
Department of Electronic & Electrical Engineering, University of Surrey, Guildford, Surrey GU2 5XH, United Kingdom
Abstract :
A non-parametric probability density function (pdf) estimation technique is presented. The estimation consists in approximating the unknown pdf by a network of Gaussian Radial Basis Functions (GRBFs). Complexity analysis is introduced in order to select the optimal number of GRBFs. Results obtained on real data show the potentiality of this technique.
Keywords :
Complexity theory; Computer architecture; Estimation; Iris; Neurons; Probability density function; Training;
Conference_Titel :
European Signal Processing Conference, 1996. EUSIPCO 1996. 8th
Conference_Location :
Trieste, Italy
Print_ISBN :
978-888-6179-83-6
