Evidence map›Paper›PMID 31983922›Full record

ArticleEURASIP journal on advances in signal processing2019

Stationary time-vertex signal processing.

Andreas Loukas, Nathanaël Perraudin

Abstract read
In one paragraph

Article in EURASIP journal on advances in signal processing, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Andreas Loukas *1Laboratoire de Traitement des Signaux 2, École Polytechnique Fédérale Lausanne, Lausanne, 1015 Switzerland.
Nathanaël Perraudin *2Swiss Data Science Center, Eidgenössische Technische Hochschule Zürich, Universitätstrasse 25, Zürich, 8006 Switzerland.ORCID 0000-0001-8285-1308

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper considers regression tasks involving high-dimensional multivariate processes whose structure is dependent on some known graph topology. We put forth a new definition of time-vertex wide-sense stationarity, or

Indexed as

Graph signal processingHarmonic analysisMultivariate time-vertex processesPSD estimationStationarity

Identifiers

PMID31983922
PMCPMC6951473

What OpenQuestion holds

Textmetadata
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.