Matrix decomposition and multiple source location

Di, Angzhao; Tian, Lisheng

doi:10.1109/icassp.1984.1172651

Cited by 9 publications

(1 citation statement)

References 2 publications

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“…Chen et al ( 1991 ) proposed a method that detected the number of sources by imposing an upper bound on the eigenvalue magnitudes of the correlation matrix derived from the array output. In addition to conventional eigenvalue-based techniques, a few methods have also employed eigenvectors for estimating the number of sources (Di and Tian, 1984 ; Jiang and Ingram, 2004 ).…”

Section: Introductionmentioning

confidence: 99%

An F-ratio-based method for estimating the number of active sources in MEG

Giri,

Mosher,

Adler

et al. 2023

Front. Hum. Neurosci.

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IntroductionMagnetoencephalography (MEG) is a powerful technique for studying the human brain function. However, accurately estimating the number of sources that contribute to the MEG recordings remains a challenging problem due to the low signal-to-noise ratio (SNR), the presence of correlated sources, inaccuracies in head modeling, and variations in individual anatomy.MethodsTo address these issues, our study introduces a robust method for accurately estimating the number of active sources in the brain based on the F-ratio statistical approach, which allows for a comparison between a full model with a higher number of sources and a reduced model with fewer sources. Using this approach, we developed a formal statistical procedure that sequentially increases the number of sources in the multiple dipole localization problem until all sources are found.ResultsOur results revealed that the selection of thresholds plays a critical role in determining the method's overall performance, and appropriate thresholds needed to be adjusted for the number of sources and SNR levels, while they remained largely invariant to different inter-source correlations, translational modeling inaccuracies, and different cortical anatomies. By identifying optimal thresholds and validating our F-ratio-based method in simulated, real phantom, and human MEG data, we demonstrated the superiority of our F-ratio-based method over existing state-of-the-art statistical approaches, such as the Akaike Information Criterion (AIC) and Minimum Description Length (MDL).DiscussionOverall, when tuned for optimal selection of thresholds, our method offers researchers a precise tool to estimate the true number of active brain sources and accurately model brain function.

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Section: Introductionmentioning

confidence: 99%

An F-ratio-based method for estimating the number of active sources in MEG

Giri,

Mosher,

Adler

et al. 2023

Front. Hum. Neurosci.

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Wideband coherent sources localization based on a two-node distributed sensor networks

Zhang

Wang

2016

Signal Processing

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Direction‐of‐arrival estimation for uncorrelated and coherent signals in the presence of multipath propagation

Gan

Luo

2013

IET Microwaves, Antennas & Propagation

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The authors propose a novel direction-of-arrival (DOA) estimation method for signals that are uncorrelated, partially coherent or fully coherent in the presence of multipath propagation. First, uncorrelated and coherent signals are distinguished by the rotational invariance techniques as well as the property of the moduli of eigenvalues. The DOAs of the uncorrelated signals are then estimated based on their related eigenvalues. Finally, the singular value decomposition of virtual steering vectors is used to estimate the DOAs of the coherent signals while avoiding the cross-term effects. The effectiveness and efficiency of the proposed method are demonstrated by the simulation results.

show abstract

Matrix decomposition and multiple source location

Cited by 9 publications

References 2 publications

An F-ratio-based method for estimating the number of active sources in MEG

An F-ratio-based method for estimating the number of active sources in MEG

Wideband coherent sources localization based on a two-node distributed sensor networks

Direction‐of‐arrival estimation for uncorrelated and coherent signals in the presence of multipath propagation

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