Radial Basis Function Neural Network and Application to Data Interpolation

Abstract

Abstract: Neural network with radial basis function (RBF) is a new forward neural network proposed by Broomhead in 1988. It is of ad-vantage of fast computation and meeting regional optimizing demand, compared with common enor back- propagation network. In recent years it becomes of more interests and is introduced into computation of approxinating function interpolation. This paper presents the principle of neural network with RBF and the practicable interpolating computation. Case study shows it runs fast and reliably.

Key words: neural network, function, interpolation, computation

CLC Number:

TE319

YANG Yan-jun, YANG Yu, KANG Zhi-hong. Radial Basis Function Neural Network and Application to Data Interpolation[J]. Xinjiang Petroleum Geology, 2005, 26(2): 209-211.

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Radial Basis Function Neural Network and Application to Data Interpolation

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