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Record W1900853877 · doi:10.1109/iscas.2002.1010734

An improved ROM compression technique for direct digital frequency synthesizers

2003· article· en· W1900853877 on OpenAlexaff
M.M. El Said, Mohamed Elmasry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceDirect digital synthesizerCompression (physics)Data compressionElectronic engineeringFrequency synthesizerTelecommunicationsPhase-locked loopMaterials scienceAlgorithmEngineeringJitter

Abstract

fetched live from OpenAlex

In this paper a comparison between the famous ROM compression techniques, for ROM-based direct digital frequency synthesizers, was performed. Inaccuracies of previous comparisons are pointed out. An improved ROM compression technique based on the Taylor-series linear interpolation method, developed by Bellaouar et al. (see IEEE J Solid-State Circuits, vol. 35, no. 3, p. 385-390, 2000), is presented. Simulation results show that compared to previously reported compression techniques, this improvement can achieve considerable reductions in the ROM size.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.239
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations27
Published2003
Admission routes1
Has abstractyes

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