Detecting the Number of EMI Sources Based on Higher Order Statistics

Song, Zhenfei; Su, Donglin; Xie, Shuguo

doi:10.1109/emczur.2009.4783491

Cited by 5 publications

(1 citation statement)

References 10 publications

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“…In the second group, the number of the sources is estimated by analyzing attributes of the signals. In [8], the authors directly applied Higher Order Statistics (HOS) method, which is also widely used in BSS problem [12], to observations to estimate the source number. These approaches could get quite fine result on the linear mixing situation.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Signal Sources Estimation Based on Nonlinear Dimension Reduction

Li¹,

Ma²,

Zhao³

2018

dtetr

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The estimation on signal source number is an important research issue in the field of signal analysis, especially in electromagnetic compatibility (EMC) under complex environments. Due to the nonlinear nature of electromagnetic interference (EMI), traditional linear methods usually take a bad performance. In this paper, we propose an estimation method by combining the ICA and nonlinear dimension reduction. Our experimental results show that the proposed algorithm outperforms methods for comparison under nonlinear condition.

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Section: Introductionmentioning

confidence: 99%

Nonlinear Signal Sources Estimation Based on Nonlinear Dimension Reduction

Li¹,

Ma²,

Zhao³

2018

dtetr

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An EMI radiation grouping approach based on spectral cluster in near filed scanning for assessment

Huang

Gao

et al. 2021

IOP Conf. Ser.: Mater. Sci. Eng.

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With the ever-increasing operating frequency in integrated circuit, it is very essentialto assess the radiation used to help the IC designer. Based on the similarity of electromagnetic patterns obtained from the radiation of ICs and their nonlinear edge, we develop a post-processing technique to group the electromagnetic patterns. A near field scanning is performed to obtain and extract the electromagnetic pattern that is used to validate the technique. Experiment results show that it can accurately group the electromagnetic patterns by which radiation assessment can be performed.

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A novel electromagnetic radiated emission source identification methodology

Song

Dai

et al. 2010

2010 Asia-Pacific International Symposium on Electromagnetic Compatibility

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Detecting the Number of EMI Sources Based on Higher Order Statistics

Cited by 5 publications

References 10 publications

Nonlinear Signal Sources Estimation Based on Nonlinear Dimension Reduction

Nonlinear Signal Sources Estimation Based on Nonlinear Dimension Reduction

An EMI radiation grouping approach based on spectral cluster in near filed scanning for assessment

A novel electromagnetic radiated emission source identification methodology

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