Two-dimensional feed-forward functionally expanded neural network

Author

Panagopoulos, Spyros ; Soraghan, John J.

Author_Institution

Dept. of Electron. & Electr. Eng., Univ. of Strathclyde, Glasgow, UK

fYear

2002

fDate

3-6 Sept. 2002

Firstpage

1

Lastpage

4

Abstract

This paper is concerned with the development of a two-dimensional feed-forward functionally expanded neural network (2D FFENN) surface modeler. New nonlinear surface basis functions are proposed for the network´s functional expansion. A network optimization technique based on an iterative function selection strategy is also described. Comparative simulation results for surface mappings generated by the 2D FFENN, Multi-layered Perceptron (MLP) and Radial Basis Function (RBF) architectures are presented.

Keywords

multilayer perceptrons; optimisation; radial basis function networks; 2D FFENN surface modeler; MLP; RBF architecture; iterative function selection strategy; multilayered perceptron; network functional expansion; network optimization technique; nonlinear surface basis functions; radial basis function architecture; surface mappings; two-dimensional feed-forward functionally expanded neural network; Approximation methods; Biological neural networks; Computational modeling; Neurons; Radial basis function networks; Sea surface; Training;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference, 2002 11th European

Conference_Location

Toulouse

ISSN

2219-5491

Type

conf

Filename

7071912