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}
}
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

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