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Modeling of complex-valued Wiener systems using B-spline neural network

Modeling of complex-valued Wiener systems using B-spline neural network
Modeling of complex-valued Wiener systems using B-spline neural network
In this brief, a new complex-valued B-spline neural network is introduced in order to model the complex-valued Wiener system using observational input/output data. The complex-valued nonlinear static function in the Wiener system is represented using the tensor product from two univariate Bspline neural networks, using the real and imaginary parts of the system input. Following the use of a simple least squares parameter initialization scheme, the Gauss–Newton algorithm is applied for the parameter estimation, which incorporates the De Boor algorithm, including both the B-spline curve and the first-order derivatives recursion. Numerical examples, including a nonlinear high-power amplifier model in communication systems, are used to demonstrate the efficacy of the proposed approaches.
818-825
Hong, Xia
e6551bb3-fbc0-4990-935e-43b706d8c679
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hong, Xia
e6551bb3-fbc0-4990-935e-43b706d8c679
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80

Hong, Xia and Chen, Sheng (2011) Modeling of complex-valued Wiener systems using B-spline neural network. IEEE Transactions on Neural Networks, 22 (5), 818-825.

Record type: Article

Abstract

In this brief, a new complex-valued B-spline neural network is introduced in order to model the complex-valued Wiener system using observational input/output data. The complex-valued nonlinear static function in the Wiener system is represented using the tensor product from two univariate Bspline neural networks, using the real and imaginary parts of the system input. Following the use of a simple least squares parameter initialization scheme, the Gauss–Newton algorithm is applied for the parameter estimation, which incorporates the De Boor algorithm, including both the B-spline curve and the first-order derivatives recursion. Numerical examples, including a nonlinear high-power amplifier model in communication systems, are used to demonstrate the efficacy of the proposed approaches.

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Published date: May 2011
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 272266
URI: https://eprints.soton.ac.uk/id/eprint/272266
PURE UUID: fb264e83-ebbb-4e6c-8072-e89dc960e9f7

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Date deposited: 09 May 2011 14:05
Last modified: 18 Jul 2017 06:32

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Contributors

Author: Xia Hong
Author: Sheng Chen

University divisions

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