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Record W3212996010 · doi:10.1109/tcsii.2021.3125568

A Memory-Based Direct-Digital Frequency Synthesizer for Fractional Synchronization

2021· article· en· W3212996010 on OpenAlexaff
Soheyl Ziabakhsh, Sadok Aouini, Robert G. Gibbins, Matt Mikkelsen, Sanam Moslemi-Tabrizi, Naim Ben‐Hamida

Bibliographic record

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsCiena (Canada)
Fundersnot available
KeywordsJitterComputer scienceDirect digital synthesizerComputer hardwareElectronic engineeringPhase-locked loopEngineeringFrequency synthesizerTelecommunications

Abstract

fetched live from OpenAlex

This brief presents a fully integrated energy-efficient memory-based direct digital frequency synthesizer (DDFS). To overcome the limitation of using an accumulator and a Read-Only Memory (ROM) Lookup Table (LUT) within a DDFS, the proposed design utilizes a 6-bit memory with a configured mode of operation to synchronize the digital output clock with the input sampling clock. The proposed DDFS is able to tune the output phase and frequency once a phase rotator is used in the input clock path. To realize the proposed DDFS, a 6-bit memory in front-end and some analog blocks in back-end are employed. The prototype DDFS achieves jitter below 12.7ps <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{rms}$ </tex-math></inline-formula> integrated over a 100MHz bandwidth with 28.25Hz resolution while consuming less than 3mW at sampling clock 3.12GHz. The proposed DDFS is fabricated in a 0.9V TSMC 7nm CMOS process and occupies a core area of only 0.014mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score1.000

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 head0.015
GPT teacher head0.224
Teacher spread0.209 · 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.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations13
Published2021
Admission routes1
Has abstractyes

Explore more

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