Evidence map›Paper›PMID 36679659›Full record

ArticleSensors (Basel, Switzerland)2023

Over the Limits of Traditional Sampling: Advantages and Issues of AICs for Measurement Instrumentation.

Grazia Iadarola, Pasquale Daponte, Luca De Vito, Sergio Rapuano

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Grazia IadarolaDepartment of Information Engineering, Polytechnic University of Marche, 60131 Ancona, Italy.ORCID 0000-0001-7093-2733
Pasquale DaponteDepartment of Engineering, University of Sannio, 82100 Benevento, Italy.ORCID 0000-0002-5215-3661
Luca De VitoDepartment of Engineering, University of Sannio, 82100 Benevento, Italy.ORCID 0000-0003-1896-2614
Sergio RapuanoDepartment of Engineering, University of Sannio, 82100 Benevento, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data acquisition systems have shown the need of wideband spectrum monitoring for many years. This paper describes and discusses a recently proposed architecture aimed at acquiring efficiently wideband signals, named the Analog-to-Information Converter (AIC). AIC framework and working principle implementing the sub-Nyquist sampling are analyzed in general terms. Attention is specifically focused on the idea of exploiting the condition of the signals that, despite their large bandwidth, have a small information content in the frequency domain. However, as clarified in the paper, employing AICs in measurement instrumentation necessarily entails their characterization, through the analysis of their building blocks and the corresponding non-idealities, in order to improve the signal reconstruction.

Indexed as

Datasets as TopicAnalog-to-Information ConverterCompressive Samplingdata compressionmeasurement instrumentationmetrological characterizationsparse signalssub-Nyquist samplingwideband acquisition

Identifiers

PMID36679659
PMCPMC9863968

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.