Strathprints logo
Strathprints Home | Open Access | Browse | Search | User area | Copyright | Help | Library Home | SUPrimo

Surface approximation using the 2D FFENN architecture

Panagopolous, S. and Soraghan, J.J. (2004) Surface approximation using the 2D FFENN architecture. EURASIP Journal on Advances in Signal Processing, 2004 (17). pp. 2696-2704. ISSN 1110-8657

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

A new two-dimensional feed-forward functionally expanded neural network (2D FFENN) used to produce surface models in two dimensions is presented. New nonlinear multilevel 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, multilevel 2D FFENN, multilayered perceptron (MLP), and radial basis function (RBF) architectures are presented.

Item type: Article
ID code: 7115
Keywords: neural networks, sea clutter, surface modelling, signal processing, Electrical engineering. Electronics Nuclear engineering
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
Unknown Department
Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 05 Nov 2008
    Last modified: 16 Jul 2013 20:01
    URI: http://strathprints.strath.ac.uk/id/eprint/7115

    Actions (login required)

    View Item