Evidence map›Paper›PMID 27736959›Full record

ArticlePloS one2016

Improvement of Source Number Estimation Method for Single Channel Signal.

Zhi Dong, Junpeng Hu, Bolun Du, Yunze He

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Zhi DongCollege of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, Hunan Province, China.
Junpeng HuCollege of Mechatronics and Automation, National University of Defense Technology, Changsha 410073, Hunan Province, China.
Bolun DuCollege of Electrical and Information Engineering, Hunan University, Changsha, 410082, China.
Yunze HeCollege of Electrical and Information Engineering, Hunan University, Changsha, 410082, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Source number estimation methods for single channel signal have been investigated and the improvements for each method are suggested in this work. Firstly, the single channel data is converted to multi-channel form by delay process. Then, algorithms used in the array signal processing, such as Gerschgorin's disk estimation (GDE) and minimum description length (MDL), are introduced to estimate the source number of the received signal. The previous results have shown that the MDL based on information theoretic criteria (ITC) obtains a superior performance than GDE at low SNR. However it has no ability to handle the signals containing colored noise. On the contrary, the GDE method can eliminate the influence of colored noise. Nevertheless, its performance at low SNR is not satisfactory. In order to solve these problems and contradictions, the work makes remarkable improvements on these two methods on account of the above consideration. A diagonal loading technique is employed to ameliorate the MDL method and a jackknife technique is referenced to optimize the data covariance matrix in order to improve the performance of the GDE method. The results of simulation have illustrated that the performance of original methods have been promoted largely.

Indexed as

AlgorithmsModels, TheoreticalNormal Distribution

Identifiers

PMID27736959
PMCPMC5063408

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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.