Enhancing the reliability of spectral correlation function with distributed computing
Many random time series used in signal processing systems are cyclostationary due to the sinusoidal carriers, pulse trains, periodic motion, or physical phenomenon. The cyclostationarity of the signal could be analysed by using the spectral correlation function (SCF). However, it is considered high...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/31943/ http://irep.iium.edu.my/31943/1/2188.pdf http://irep.iium.edu.my/31943/4/image002.png http://irep.iium.edu.my/31943/5/icomabstracts.pdf |
| Summary: | Many random time series used in signal processing systems are cyclostationary due to the sinusoidal carriers, pulse trains, periodic motion, or physical phenomenon. The cyclostationarity of the signal could be analysed by using the spectral correlation function (SCF). However, it is considered high complex due to the 2-D functionality and the required long observation time. The SCF could be computed in various methods however, there are two methods used in practice such as FFT accumulation method (FAM) and strip spectral correlation algorithm (SSCA). This paper investigates the advantage on the complexity and the reliability by distributing the workload of one processor on different cooperated processors. The paper found that with increasing the reliability of the SCF, the number of the cooperated processors to achieve the half of the maximum complexity will reduce. |
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