Analysis of the Consecutive Mean Excision Algorithms. (3rd January 2011)
- Record Type:
- Journal Article
- Title:
- Analysis of the Consecutive Mean Excision Algorithms. (3rd January 2011)
- Main Title:
- Analysis of the Consecutive Mean Excision Algorithms
- Authors:
- Vartiainen, Johanna
Lehtomäki, Janne
Saarnisaari, Harri
Juntti, Markku - Other Names:
- Zhang Jian-Kang Academic Editor.
- Abstract:
- Abstract : The backward and forward consecutive mean excision (CME/FCME) algorithms are diagnostic methods for outlier (signal) detection. Since they are computationally simple, they have applications for both narrowband signal detection in cognitive radios and interference suppression. In this paper, a theoretical performance analysis framework of the CME algorithms is presented. The analysis provides simple tests of the detectability of the signals based on their shape in the considered domain (e.g., spectrum). As a consequence, results can be used to quickly check whether the CME/FCME algorithms are usable for a given problem or not without the need to resort to time consuming computer simulations. The computer simulations for random and orthogonal frequency division multiplexing (OFDM) signals show that the presented analysis is able to predict the detectability of signals well.
- Is Part Of:
- Journal of electrical and computer engineering. Volume 2010(2010)
- Journal:
- Journal of electrical and computer engineering
- Issue:
- Volume 2010(2010)
- Issue Display:
- Volume 2010, Issue 2010 (2010)
- Year:
- 2010
- Volume:
- 2010
- Issue:
- 2010
- Issue Sort Value:
- 2010-2010-2010-0000
- Page Start:
- Page End:
- Publication Date:
- 2011-01-03
- Subjects:
- Computer engineering -- Periodicals
Electrical engineering -- Periodicals
621.3905 - Journal URLs:
- https://www.hindawi.com/journals/jece/ ↗
- DOI:
- 10.1155/2010/459623 ↗
- Languages:
- English
- ISSNs:
- 2090-0147
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10775.xml