Abstract

Abstract. To avoid problems caused by a global multiquadric network, a local manner is considered in this work. In a local influence domain, the number of evaluation points, represented by ‘k’, is believed to play a crucial role in determining the success of the scheme. In this work, this ‘k’ is numerically investigated under a local manner of MQ-RBF neural network when applied to function approximation and recovery applications. The results discovered in this work strongly indicate that with a good combination of an MQ format and a shape-parameter choosing strategy, an optimal interval of can be located with high confidence. This piece of insight is certainly useful for further applications of the scheme.

Received: 28 March 2023

AMS Subject Classification: 33F05, 34K08, 92B20

Key Words and Phrases: local interpolation, radial basis function, multiquadric, neural network, function recovery

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How to cite this paper?
DOI: 10.12732/ijam.v36i6.2
Source: International Journal of Applied Mathematics
ISSN printed version: 1311-1728
ISSN on-line version: 1314-8060
Year: 2023
Volume: 36
Issue: 6

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