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2014 Research on Amplifier Performance Evaluation Based on δ-Support Vector Regression
Xing Huo, Aihua Zhang, Hamid Reza Karimi
Abstr. Appl. Anal. 2014: 1-6 (2014). DOI: 10.1155/2014/574547

Abstract

Focusing on the amplifier performance evaluation demand, a novel evaluation strategy based on δ-support vector regression (δ-SVR) is proposed in this paper. Lower computer calculation demand is considered firstly. And this is dealt with by the superiority of δ-SVR which can be significantly improved on the number of support vectors. Moreover, the function of δ-SVR employs the modified RBF kernel function which is constructed from an original kernel by removing the last coordinate and adding the linear term with the last coordinate. Experiment adopted the typical circuit Sallen-Key low pass filter to prove the proposed evaluation strategy via the eight performance indexes. Simulation results reveal that the need of the number of δ-SVR support vectors is the lowest among the other two methods LSSVR and ε-SVR under obtaining nearly the same evaluation result. And this is also suitable for promotion computational speed.

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Xing Huo. Aihua Zhang. Hamid Reza Karimi. "Research on Amplifier Performance Evaluation Based on δ-Support Vector Regression." Abstr. Appl. Anal. 2014 1 - 6, 2014. https://doi.org/10.1155/2014/574547

Information

Published: 2014
First available in Project Euclid: 2 October 2014

Digital Object Identifier: 10.1155/2014/574547

Rights: Copyright © 2014 Hindawi

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