Modeling of voltage source inverter having active split DC-bus for supply of four-wire electrical utility systems
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: 2014DOI: 10.1109/IranianCIS.2014.6802573
Keyword(s): Markov processes,n geophysical image processing,n image classification,n support vector machines,n AVIRIS,n ECHO,n EMP,n Kappa factor,n MRF energy function,n ROSIS,n aerial images,n agriculture images,n average accuracy,n class map visualization,n forest structure,n hyperspectral image classification,n locally weighted Markov random fields,n marginal weighting function,n overall accuracy,n probabilistic SVM classification,n sensors
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Modeling of voltage source inverter having active split DC-bus for supply of four-wire electrical utility systems
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| contributor author | Lidozzi, Alessandro | |
| contributor author | Calzo, Giovanni Lo | |
| contributor author | Pipolo, Sabino | |
| contributor author | Solero, Luca | |
| contributor author | Crescimbini, Fabio | |
| date accessioned | 2020-03-12T21:40:59Z | |
| date available | 2020-03-12T21:40:59Z | |
| date issued | 2014 | |
| identifier other | 6953514.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/1056846?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Modeling of voltage source inverter having active split DC-bus for supply of four-wire electrical utility systems | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8187983 | |
| subject keywords | Markov processes | |
| subject keywords | n geophysical image processing | |
| subject keywords | n image classification | |
| subject keywords | n support vector machines | |
| subject keywords | n AVIRIS | |
| subject keywords | n ECHO | |
| subject keywords | n EMP | |
| subject keywords | n Kappa factor | |
| subject keywords | n MRF energy function | |
| subject keywords | n ROSIS | |
| subject keywords | n aerial images | |
| subject keywords | n agriculture images | |
| subject keywords | n average accuracy | |
| subject keywords | n class map visualization | |
| subject keywords | n forest structure | |
| subject keywords | n hyperspectral image classification | |
| subject keywords | n locally weighted Markov random fields | |
| subject keywords | n marginal weighting function | |
| subject keywords | n overall accuracy | |
| subject keywords | n probabilistic SVM classification | |
| subject keywords | n sensors | |
| identifier doi | 10.1109/IranianCIS.2014.6802573 | |
| journal title | nergy Conversion Congress and Exposition (ECCE), 2014 IEEE | |
| filesize | 1673222 | |
| citations | 0 |