GAUSSIAN PROCESS MODELING OF CPW-FED SLOT ANTENNAS
@article{Villiers2009GAUSSIANPM, title={GAUSSIAN PROCESS MODELING OF CPW-FED SLOT ANTENNAS}, author={J. D. Villiers and J. P. Jacobs}, journal={Progress in Electromagnetics Research-pier}, year={2009}, volume={98}, pages={233-249} }
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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