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)Official URL: http://dx.doi.org/10.1155/S111086570440612X
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: | 04 Oct 2012 12:11 |
| URI: | http://strathprints.strath.ac.uk/id/eprint/7115 |
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