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Radial basis function neural networks: in tracking and extraction of stochastic process in forestry

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1 Author(s)
Radonja, P.J. ; Inst. of Forestry, SE Serbiaforest, Belgrade, Yugoslavia

The performances of classical approximation methods and radial-basis function (RBF) neural networks in tracking of height density data are presented in the first part of the paper. The application of the different classical approximation methods in extraction of unknown biological processes from real measured data is considered in the second part of the paper. The advantages of implementation of RBF neural networks in the extraction of unknown processes are analyzes and illustrated with an example

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Neural Network Applications in Electrical Engineering, 2000. NEUREL 2000. Proceedings of the 5th Seminar on

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