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Record W4406400350 · doi:10.1049/icp.2024.4481

Analysis of integer-N phase-locked-loop architecture

2025· article· en· W4406400350 on OpenAlexaff
Ziyu Chenguo, Z. Y. Ou, Xinyu Tao

Bibliographic record

VenueIET conference proceedings. · 2025
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLoop (graph theory)Phase (matter)Integer (computer science)ArchitectureComputer scienceMathematicsPhysicsCombinatoricsOperating systemArt

Abstract

fetched live from OpenAlex

Phase-Locked Loops have a wide range of applications as frequency synthesizers. An analysis of Integer-N Phase-Locked-Loop (PLL) is presented in this article. The performance of a phase-locked loop is determined by a number of factors. It is shown whether good locking time performance can be provided by changing the loop bandwidth of the PLL system. The loop filter can be designed to accelerate the lock time because it controls the poles and zeros of the system. The PLL system is a typical Charge-Pump PLL which uses a Ring Voltage-Controlled Oscillator (Ring-VCO) to optimize the area as much as possible and to reduce power consumption. The phase noise of the Ring-VCO at 1MHz is -96.14dBc and the system can deliver a stable output frequency of 1.6GHz with a 100MHz reference clock. The Multi-Modulus Divider (MMD) used can provide divider ratios from 16 to 31. Simulation is done by TSMC 40nm process.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.021
GPT teacher head0.306
Teacher spread0.285 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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