Evidence map›Paper›PMID 26295232›Full record

ArticleSensors (Basel, Switzerland)2015

Statistical Analysis of the Performance of MDL Enumeration for Multiple-Missed Detection in Array Processing.

Fei Du, Yibo Li, Shijiu Jin

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Fei DuState Key Laboratory of Precision Measurement Technology and Instrument, Tianjin University, Tianjin 300072, China. dukemyy@tju.edu.cn.
Yibo LiState Key Laboratory of Precision Measurement Technology and Instrument, Tianjin University, Tianjin 300072, China. slyb@tju.edu.cn.
Shijiu JinState Key Laboratory of Precision Measurement Technology and Instrument, Tianjin University, Tianjin 300072, China. shjjin@tju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An accurate performance analysis on the MDL criterion for source enumeration in array processing is presented in this paper. The enumeration results of MDL can be predicted precisely by the proposed procedure via the statistical analysis of the sample eigenvalues, whose distributive properties are investigated with the consideration of their interactions. A novel approach is also developed for the performance evaluation when the source number is underestimated by a number greater than one, which is denoted as "multiple-missed detection", and the probability of a specific underestimated source number can be estimated by ratio distribution analysis. Simulation results are included to demonstrate the superiority of the presented method over available results and confirm the ability of the proposed approach to perform multiple-missed detection analysis.

Indexed as

array processingminimum description length (MDL)multiple-missed detectionperformance analysissource enumeration

Identifiers

PMID26295232
PMCPMC4570420

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.