Using Radial Basis Function Networks for Function Approximation and Classification

Joint Authors

Du, K.-L.
Zhang, Biaobiao
Wu, Yue
Wang, Hui

Source

ISRN Applied Mathematics

Issue

Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-34, 34 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2012-03-06

Country of Publication

Egypt

No. of Pages

34

Main Subjects

Mathematics

Abstract EN

The radial basis function (RBF) network has its foundation in the conventional approximation theory.

It has the capability of universal approximation.

The RBF network is a popular alternative to the well-known multilayer perceptron (MLP), since it has a simpler structure and a much faster training process.

In this paper, we give a comprehensive survey on the RBF network and its learning.

Many aspects associated with the RBF network, such as network structure, universal approimation capability, radial basis functions, RBF network learning, structure optimization, normalized RBF networks, application to dynamic system modeling, and nonlinear complex-valued signal processing, are described.

We also compare the features and capability of the two models.

American Psychological Association (APA)

Wu, Yue& Wang, Hui& Zhang, Biaobiao& Du, K.-L.. 2012. Using Radial Basis Function Networks for Function Approximation and Classification. ISRN Applied Mathematics،Vol. 2012, no. 2012, pp.1-34.
https://search.emarefa.net/detail/BIM-463508

Modern Language Association (MLA)

Wu, Yue…[et al.]. Using Radial Basis Function Networks for Function Approximation and Classification. ISRN Applied Mathematics No. 2012 (2012), pp.1-34.
https://search.emarefa.net/detail/BIM-463508

American Medical Association (AMA)

Wu, Yue& Wang, Hui& Zhang, Biaobiao& Du, K.-L.. Using Radial Basis Function Networks for Function Approximation and Classification. ISRN Applied Mathematics. 2012. Vol. 2012, no. 2012, pp.1-34.
https://search.emarefa.net/detail/BIM-463508

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-463508