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Record W1868086354 · doi:10.1109/iscas.2001.921097

A fully digital timing recovery scheme using two samples per symbol

2002· article· en· W1868086354 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicBlind Source Separation Techniques
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSymbol rateSymbol (formal)Computer scienceInterpolation (computer graphics)Transmission (telecommunications)AlgorithmSampling (signal processing)SIGNAL (programming language)Filter (signal processing)Feature (linguistics)Artificial intelligenceComputer visionBit error rateTelecommunicationsDecoding methods

Abstract

fetched live from OpenAlex

In this paper, a new symbol timing recovery scheme is presented for digital receiver. The proposed algorithm belongs to the category of feedforward recovery and consists of two stages-phase estimation and interpolation. The phase estimation is to detect the clock phase of the sampled signal, which indicates the deviation of the reference sample from the point of maximum eye-opening. The interpolation which is implemented with an FIR filter is to reconstruct the transmitted symbols. Although many estimation algorithms have been developed in the literature, these methods usually need an input sampling rate of at least four samples per symbol. The proposed scheme requires only two samples/symbol, thus allowing the use of a very low sampling rate at the receiver. This feature is very important in the implementation of a digital receiver for high-rate transmission, since the hardware cost of the receiver depends heavily on the required processing speed.

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.

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)0.000
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: none
Teacher disagreement score0.961
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
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 head0.085
GPT teacher head0.289
Teacher spread0.205 · 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

Quick stats

Citations9
Published2002
Admission routes2
Has abstractyes

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