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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jacobs, J.P. de Villiers, D.I.L. |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Electr. & Electron. Eng., Stellenbosch Univ. Stellenbosch, Stellenbosch, South Africa (de Villiers, D.I.L.) || Dept. of Electr., Electron. & Comput. Eng.efficiency, Univ. of Pretoria, Pretoria, South Africa (Jacobs, J.P.) |
| Abstract | This paper presents a low cost Gaussian process (GP) modeling technique for antenna responses that exhibit highly oscillatory behavior as a function of frequency. Using a judiciously constructed composite covariance function that is able to capture the quasi-periodic behavior of the responses, an accurate interpolant could be established with far fewer training points than would normally be considered necessary for representing the oscillatory behaviour. The specific example investigated here is the aperture efficiency response of an offset Gregorian reflector antenna system, which has previously been shown to possess an oscillatory response which is computationally expensive to model accurately. Initial results using the suggested method are promising, with accurate interpolants of the expected response generated using only a sparse set of randomly selected training data. Notably, predictions were accurate even in sections of the response that contained multiple contiguous cycles and no training points. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 327720 |
| Page Count | 4 |
| File Format | |
| e-ISBN | 9781479989430 |
| DOI | 10.1109/LAPC.2015.7366109 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-11-02 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Training modeling Computational modeling Training data regression Gaussian processes Apertures Covariance matrices Gregorian antennas covariance function |
| Content Type | Text |
| Resource Type | Article |
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