Surface approximation using the multi-level and interpolation 2D FFENN

S. Panagopolous, J.J. Soraghan

Research output: Contribution to conferencePaper

Abstract

In this paper, we present the development of a two dimensional feed-forward functionally expanded neural network (2D FFENN) surface modeler. Two application models of the generic design are also proposed. The scope of this work is the development of a two-dimensional system able to produce surface data mappings. The main application area of interest is sea surface modeling and target detection by sea clutter suppression. New nonlinear multi-level 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. Results for surface mappings generated by the multi-level 2D FFENN and interpolation 2D FFENN designs are presented.
Original languageEnglish
Publication statusPublished - 2002
EventSignal Processing, Pattern Recognition, and Applications (SPPRA 2002) - Crete, Greece
Duration: 25 Jun 200228 Jun 2002

Conference

ConferenceSignal Processing, Pattern Recognition, and Applications (SPPRA 2002)
CountryGreece
CityCrete
Period25/06/0228/06/02

Keywords

  • neural networks
  • surface modeling
  • sea clutter
  • radar
  • surface approximation
  • multi-level
  • interpolation
  • 2d ffenn

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  • Cite this

    Panagopolous, S., & Soraghan, J. J. (2002). Surface approximation using the multi-level and interpolation 2D FFENN. Paper presented at Signal Processing, Pattern Recognition, and Applications (SPPRA 2002) , Crete, Greece.