Surface modeling using 2D FFENN

S. Panagopolous, J.J. Soraghan

Research output: Contribution to conferencePaper


This paper is concerned With the development of a two-dimensional feed-forward functionally expanded neural network (2D FFENN) surface modeller. 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.. The main purpose of this work is the. development of a two-dimensional system, able to produce surface data mappings. The main application area of interest for the proposed system is, sea surface modelling and target detection by sea clutter suppression.
Original languageEnglish
Number of pages5
Publication statusPublished - Oct 2002
EventRADAR 2002 Conference - Edinburgh, United Kingdom
Duration: 15 Oct 200217 Oct 2002


ConferenceRADAR 2002 Conference
Country/TerritoryUnited Kingdom


  • surface modeling
  • 2d ffenn


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