Research on amplifier performance evaluation based on δ-support vector regression
Journal article, Peer reviewed
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Original versionHuo, X., Zhang, A., & Karimi, H. R. (2014). Research on amplifier performance evaluation based on δ-support vector regression. Abstract and Applied Analysis, 2014. doi: 10.1155/2014/574547 10.1155/2014/574547
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.
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/574547 Open Access