• Mathematics
• Published 2009
• DOI:10.2528/PIER09083103

GAUSSIAN PROCESS MODELING OF CPW-FED SLOT ANTENNAS

@inproceedings{Villiers2009GAUSSIANPM,
  title={GAUSSIAN PROCESS MODELING OF CPW-FED SLOT ANTENNAS},
  author={Jason P. de Villiers and Jan P. A. M. Jacobs},
  year={2009}
}

• Jason P. de Villiers, Jan P. A. M. Jacobs

Gaussian process (GP) regression is proposed as a structured supervised learning alternative to neural networks for the modeling of CPW-fed slot antenna input characteristics. A Gaussian process is a stochastic process and entails the generalization of the Gaussian probability distribution to functions. Standard GP regression is applied to modeling S11 against frequency of a CPW-fed second- resonant slot dipole, while an approximate method for large datasets is applied to an ultrawideband (UWB… CONTINUE READING

View PDF

Save to Library

Create Alert

Cite