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Record W2165989345 · doi:10.1109/ccece.1995.528172

An on-line method for signal recovery from nonuniform samples using block-rearrangement

2002· article· en· W2165989345 on OpenAlexaff
José Luis Romero, E.I. Plotkin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicImage and Signal Denoising Methods
Canadian institutionsConcordia University
Fundersnot available
KeywordsBlock (permutation group theory)SIGNAL (programming language)AlgorithmLine (geometry)Singular value decompositionIterative methodSignal recoveryMathematicsSample (material)Computer scienceSignal processingMathematical optimizationCompressed sensingCombinatoricsTelecommunicationsGeometryChromatographyChemistry

Abstract

fetched live from OpenAlex

A method for the signal recovery from nonuniform samples based on the block rearrangement of the sample ensemble is presented. The proposed method belongs to the class of on-line procedures because of the use of block processing that permits a fast start without waiting for additional information. The method consists of three basic stages. In the first stage, a rearrangement of the samples takes place by which they are allocated in blocks. In the second stage, an estimate of the corresponding uniform samples is obtained. The third stage consists in the successive application of an iterative procedure that improves the preliminary estimate of the uniform samples, by correcting the values of the nonuniform samples calculated from the estimate of the uniform samples. To obtain the estimate, two different methods are used: one based on the solution of systems of linear equations, and another one based on singular value decomposition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.897
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.129
GPT teacher head0.353
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2002
Admission routes1
Has abstractyes

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