Bayesian Nonparametric Modeling for Rapid Design of Metamaterial Microstructures
We consider the problem of rapid design of massive metamaterial (MTM) microstructures from a statistical point of view. A Bayesian nonparametric model, namely, Gaussian Process (GP) mixture, is developed to generate the mapping relationship from the microstructure’s geometric dimension to the electr...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2014/165102 |
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| _version_ | 1832561744144236544 |
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| author | Bin Liu Chunlin Ji |
| author_facet | Bin Liu Chunlin Ji |
| author_sort | Bin Liu |
| collection | DOAJ |
| description | We consider the problem of rapid design of massive metamaterial (MTM) microstructures from a statistical point of view. A Bayesian nonparametric model, namely, Gaussian Process (GP) mixture, is developed to generate the mapping relationship from the microstructure’s geometric dimension to the electromagnetic response, which is approximately expressed in a closed form of Drude-Lorentz type model. This GP mixture model is neatly able to tackle nonstationarity, discontinuities in the mapping function. The inference is performed using a Markov chain relying on Gibbs sampling. Experimental results demonstrate that the proposed approach is highly efficient in facilitating rapid design of MTM with accuracy. |
| format | Article |
| id | doaj-art-f4f1a1d4e65b46b4a0822a62ed62828c |
| institution | Kabale University |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-f4f1a1d4e65b46b4a0822a62ed62828c2025-02-03T01:24:20ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772014-01-01201410.1155/2014/165102165102Bayesian Nonparametric Modeling for Rapid Design of Metamaterial MicrostructuresBin Liu0Chunlin Ji1School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, ChinaShenzhen Kuang-Chi Institute of Advanced Technology, Shenzhen 518057, ChinaWe consider the problem of rapid design of massive metamaterial (MTM) microstructures from a statistical point of view. A Bayesian nonparametric model, namely, Gaussian Process (GP) mixture, is developed to generate the mapping relationship from the microstructure’s geometric dimension to the electromagnetic response, which is approximately expressed in a closed form of Drude-Lorentz type model. This GP mixture model is neatly able to tackle nonstationarity, discontinuities in the mapping function. The inference is performed using a Markov chain relying on Gibbs sampling. Experimental results demonstrate that the proposed approach is highly efficient in facilitating rapid design of MTM with accuracy.http://dx.doi.org/10.1155/2014/165102 |
| spellingShingle | Bin Liu Chunlin Ji Bayesian Nonparametric Modeling for Rapid Design of Metamaterial Microstructures International Journal of Antennas and Propagation |
| title | Bayesian Nonparametric Modeling for Rapid Design of Metamaterial Microstructures |
| title_full | Bayesian Nonparametric Modeling for Rapid Design of Metamaterial Microstructures |
| title_fullStr | Bayesian Nonparametric Modeling for Rapid Design of Metamaterial Microstructures |
| title_full_unstemmed | Bayesian Nonparametric Modeling for Rapid Design of Metamaterial Microstructures |
| title_short | Bayesian Nonparametric Modeling for Rapid Design of Metamaterial Microstructures |
| title_sort | bayesian nonparametric modeling for rapid design of metamaterial microstructures |
| url | http://dx.doi.org/10.1155/2014/165102 |
| work_keys_str_mv | AT binliu bayesiannonparametricmodelingforrapiddesignofmetamaterialmicrostructures AT chunlinji bayesiannonparametricmodelingforrapiddesignofmetamaterialmicrostructures |