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Sample reduction during signal detection using difference sets and almost difference sets
Thesis (MEng(Electronic Engineering))--University of Pretoria, 2019.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2019
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| _version_ | 1867613629567729664 |
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| access_status_str | Open Access |
| author2 | Du Plessis, Warren Paul |
| author_browse | Du Plessis, Warren Paul |
| author_facet | Du Plessis, Warren Paul |
| collection | Thesis |
| dc_rights_str_mv | © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Thesis (MEng(Electronic Engineering))--University of Pretoria, 2019. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/71132 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:39:11.459Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/71132 Sample reduction during signal detection using difference sets and almost difference sets Du Plessis, Warren Paul waderaysmith@gmail.com Smith, Wade Raymond Signal detection Non-uniform sampling Difference sets Almost difference sets Sub-Nyquist sampling Thesis (MEng(Electronic Engineering))--University of Pretoria, 2019. Wide signal bandwidths typically require receivers performing signal detection to collect very large quantities of data. However, in applications with limited size, weight and power (SWAP) requirements, reducing the amount of data becomes important for proper operation. Most existing sample reduction approaches rely on reconstruction algorithms to compensate for the missing data, but these are often computationally complex. Therefore, in this work sample reduction without reconstruction is considered. This work proposes an approach to discarding samples prior to detection using difference sets (DSs) and almost difference sets (ADSs) – exploiting their sidelobe and cyclic properties – to minimise the negative impact on detection performance. Included are mathematical analyses, simulations, and experiments with practical data evaluating the effects of this technique on the detection performance. This work demonstrates that while the lack of a reconstruction algorithm does introduce interference, this is reduced when using DSs and ADSs compared to when samples are discarded at random, and the use of these sets allows predictions about performance to be made beforehand using only the set parameters. Additionally, the proposed technique performs much faster than detection with reconstruction, while having a reasonable decrease in detection performance. GEW Electrical, Electronic and Computer Engineering MEng(Electronic Engineering) Unrestricted 2019-08-19T10:28:46Z 2019-08-19T10:28:46Z 2019-09-02 2019 Dissertation * S2019 http://hdl.handle.net/2263/71132 en © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | Signal detection Non-uniform sampling Difference sets Almost difference sets Sub-Nyquist sampling Sample reduction during signal detection using difference sets and almost difference sets |
| title | Sample reduction during signal detection using difference sets and almost difference sets |
| title_full | Sample reduction during signal detection using difference sets and almost difference sets |
| title_fullStr | Sample reduction during signal detection using difference sets and almost difference sets |
| title_full_unstemmed | Sample reduction during signal detection using difference sets and almost difference sets |
| title_short | Sample reduction during signal detection using difference sets and almost difference sets |
| title_sort | sample reduction during signal detection using difference sets and almost difference sets |
| topic | Signal detection Non-uniform sampling Difference sets Almost difference sets Sub-Nyquist sampling |
| url | http://hdl.handle.net/2263/71132 |