Analysis of nonstationary emissions for efficient characterization of stochastic EM fields
A statistical approach using field-field correlation functions which is obtained from two-probe time domain measurement is used to characterize the radiation from complex devices. The time-frequency analysis provided by the measurement data has shown that significant emissions may only occur for a f...
| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/51966/ |
| _version_ | 1848798615260102656 |
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| author | Baharuddin, Mohd Hafiz Smartt, Chris Maricar, Mohamed Ismaeel Thomas, David W.P. Gradoni, Gabriele Creagh, Stephen C. Tanner, Gregor |
| author_facet | Baharuddin, Mohd Hafiz Smartt, Chris Maricar, Mohamed Ismaeel Thomas, David W.P. Gradoni, Gabriele Creagh, Stephen C. Tanner, Gregor |
| author_sort | Baharuddin, Mohd Hafiz |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | A statistical approach using field-field correlation functions which is obtained from two-probe time domain measurement is used to characterize the radiation from complex devices. The time-frequency analysis provided by the measurement data has shown that significant emissions may only occur for a few percent of the time and a piecewise stationary model of emissions may be most appropriate. In this paper, a sorting technique is applied to short time segments of the nonstationary time-domain data provided by the measurements. These short time segments are sorted into groups according to the characteristics of the emissions, i.e. different emission processes, with the assumption that the stochastic emissions is stationary within each group (process). The ensemble of time segments associated with each group may then be used to obtain the fieldfield correlations for each process. Results of the analysis give promising insights into how to characterize complex and time dependent systems. |
| first_indexed | 2025-11-14T20:22:35Z |
| format | Conference or Workshop Item |
| id | nottingham-51966 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:22:35Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-519662018-08-31T07:38:18Z https://eprints.nottingham.ac.uk/51966/ Analysis of nonstationary emissions for efficient characterization of stochastic EM fields Baharuddin, Mohd Hafiz Smartt, Chris Maricar, Mohamed Ismaeel Thomas, David W.P. Gradoni, Gabriele Creagh, Stephen C. Tanner, Gregor A statistical approach using field-field correlation functions which is obtained from two-probe time domain measurement is used to characterize the radiation from complex devices. The time-frequency analysis provided by the measurement data has shown that significant emissions may only occur for a few percent of the time and a piecewise stationary model of emissions may be most appropriate. In this paper, a sorting technique is applied to short time segments of the nonstationary time-domain data provided by the measurements. These short time segments are sorted into groups according to the characteristics of the emissions, i.e. different emission processes, with the assumption that the stochastic emissions is stationary within each group (process). The ensemble of time segments associated with each group may then be used to obtain the fieldfield correlations for each process. Results of the analysis give promising insights into how to characterize complex and time dependent systems. 2018-08-28 Conference or Workshop Item PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/51966/1/EMC%20Europe%202018_final.pdf Baharuddin, Mohd Hafiz, Smartt, Chris, Maricar, Mohamed Ismaeel, Thomas, David W.P., Gradoni, Gabriele, Creagh, Stephen C. and Tanner, Gregor (2018) Analysis of nonstationary emissions for efficient characterization of stochastic EM fields. In: International Symposium and Exhibition on Electromagnetic Compatibility (EMC EUROPE 2018), 27-30 Aug 2018, Amsterdam, Netherlands. Nonstationary time domain data; Radiated emissions;Printed circuit boards; Piecewise stationary data; Time domain measurement; Segmentation technique; Sorting technique |
| spellingShingle | Nonstationary time domain data; Radiated emissions;Printed circuit boards; Piecewise stationary data; Time domain measurement; Segmentation technique; Sorting technique Baharuddin, Mohd Hafiz Smartt, Chris Maricar, Mohamed Ismaeel Thomas, David W.P. Gradoni, Gabriele Creagh, Stephen C. Tanner, Gregor Analysis of nonstationary emissions for efficient characterization of stochastic EM fields |
| title | Analysis of nonstationary emissions for efficient characterization of stochastic EM fields |
| title_full | Analysis of nonstationary emissions for efficient characterization of stochastic EM fields |
| title_fullStr | Analysis of nonstationary emissions for efficient characterization of stochastic EM fields |
| title_full_unstemmed | Analysis of nonstationary emissions for efficient characterization of stochastic EM fields |
| title_short | Analysis of nonstationary emissions for efficient characterization of stochastic EM fields |
| title_sort | analysis of nonstationary emissions for efficient characterization of stochastic em fields |
| topic | Nonstationary time domain data; Radiated emissions;Printed circuit boards; Piecewise stationary data; Time domain measurement; Segmentation technique; Sorting technique |
| url | https://eprints.nottingham.ac.uk/51966/ |