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PSO assisted NURB Neural Network Identification

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Hong, X. and Chen, S. (2012) PSO assisted NURB Neural Network Identification. In: ICIC 2012: the Eighth International Conference on Intelligent Computing, 25-29 July 2012, Huangshan, China.

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Official URL: http://dx.doi.org/10.1007/978-3-642-31588-6_1

Abstract/Summary

A system identification algorithm is introduced for Hammerstein systems that are modelled using a non-uniform rational B-spline (NURB) neural network. The proposed algorithm consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples are utilized to demonstrate the efficacy of the proposed approach.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
ID Code:28183
Uncontrolled Keywords:B-spline NURB neural networks De Boor algorithm Hammerstein model pole assignment controller particle swarm optimization system identification
Additional Information:Intelligent Computing Technology Lecture Notes in Computer Science Volume 7389, 2012, pp 1-9
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