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Subset selection for tuning of hyper-parameters in artificial neural networks
(IEEE, 2017)
Hyper-parameters of a machine learning architecture define its design. Tuning of hyper-parameters is costly and for large data sets outright impractical, whether it is performed manually or algorithmically. In this study ...
A frequency transformation based real frequency design approach for dual-band matching
(IEEE, 2017)
This work describes a real frequency design approach for dual-band matching networks. The proposed design technique employs a direct low-pass to dual pass band frequency transformation in the scattering based real frequency ...