Evidence map›Paper›PMID 27462482›Full record

ArticleSpringerPlus2016

Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays.

Ling Liu, Ailong Wu, Xingguo Song

Abstract read
In one paragraph

Article in SpringerPlus, 2016. 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.

Ling LiuCollege of Mathematics and Statistics, Hubei Normal University, Huangshi, 435002 China.
Ailong WuCollege of Mathematics and Statistics, Hubei Normal University, Huangshi, 435002 China.
Xingguo SongSchool of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article is concerned with the global [Formula: see text] stabilization for a class of fractional-order memristive neural networks with time delays (FMDNNs). Two kinds of control scheme (i.e., state feedback control law and output feedback control law) are employed to stabilize a class of FMDNNs. Several stabilization conditions in form of algebraic criteria are presented based on a new fractional-order Lyapunov function method and Leibniz rule. Some examples are given to substantiate the effectiveness of the presented theoretical results.

Indexed as

Fractional-order systemsGlobal [Formula: see text] stabilizationMemristive neural networks

Identifiers

PMID27462482
PMCPMC4938841

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.