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Record W1973104408 · doi:10.1109/ccece.2013.6567766

Performance of unique word timing offset estimator

2013· article· en· W1973104408 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsComputer scienceOffset (computer science)EstimatorWord (group theory)Speech recognitionNatural language processingStatisticsMathematicsProgramming language

Abstract

fetched live from OpenAlex

A quadrature amplitude modulation receiver must include a timing recovery circuit to identify the correct points in time to sample the output. Timing recovery is handled differently in synchronous systems than it is in burst mode systems. In synchronous systems the convergence (or dwell) time can be quite long without penalty. In burst mode systems timing must be recovered rapidly and is therefore aided by placing a unique word at the beginning of the preamble. The output of the matched filter is correlated with the unique word to find the timing offset required to align the time origin. This timing offset is used as the “delay” input to the fractional delay filter that synchronizes the signal in the receiver to the timebase [1][3][5]. This paper discusses the performance of the timing recovery circuit using a specific unique word: length-11 Barker sequence preceded by a cyclic prefix.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.205

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 communication0.0000.001
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 head0.032
GPT teacher head0.260
Teacher spread0.227 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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