Variance estimation in neutron coincidence counting using the bootstrap method

Dubi, C.; Ocherashvilli, A.; Ettegui, H.; Pedersen, B.

doi:10.1016/j.nima.2015.05.025

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…Bootstrap is another kind of technique arising in recent years which can be used with only a few samples [24][25][26][27][28][29][30]; some scholars highlighted the motivation for using the Bootstrap in signal processing [31,32]. For signal number estimation, it needs to calculate the number of the minimum equal eigenvalues of the sampling covariance matrix based on the multiple hypothesis test, and it has a higher precision comparing with information theoretic criteria under the same circumstance.…”

Section: Introductionmentioning

confidence: 99%

Detection of Wideband Signal Number Based on Bootstrap Resampling

Zhen

2016

International Journal of Antennas and Propagation

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Knowing source number correctly is the precondition for most spatial spectrum estimation methods; however, many snapshots are needed when we determine number of wideband signals. Therefore, a new method based on Bootstrap resampling is proposed in this paper. First, signals are divided into some nonoverlapping subbands; apply coherent signal methods (CSM) to focus them on the single frequency. Then, fuse the eigenvalues with the corresponding eigenvectors of the focused covariance matrix. Subsequently, use Bootstrap to construct the new resampling matrix. Finally, the number of wideband signals can be calculated with obtained vector sequences according to clustering technique. The method has a high probability of success under low signal to noise ratio (SNR) and small number of snapshots.

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