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Record W1973070989 · doi:10.1109/tcsi.2011.2161411

Anti-Imaging Time-Mode Filter Design Using a PLL Structure With Transfer Function DFT

2011· article· en· W1973070989 on OpenAlexaff
Sadok Aouini, Kun Chuai, Gordon W. Roberts

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhase-locked loopVoltage-controlled oscillatorElectronic engineeringTransfer functionPhase noiseDelta-sigma modulationSettling timeLow-pass filterPLL multibitBandwidth (computing)Time domainNoise shapingControl theory (sociology)Filter (signal processing)Filter designComputer scienceEngineeringStep responseVoltageElectrical engineeringTelecommunicationsCMOS

Abstract

fetched live from OpenAlex

This paper presents a pole-zero placement approach for designing arbitrary-order time-mode filters for anti-imaging (reconstruction) applications. One application is for phase-domain sigma-delta modulation involving digital-to-time converters. The time-mode filters are constructed from an th-order type-II PLL single-loop feedback structure involving an active loop filter of order . The tradeoffs in terms of PLL order, noise bandwidth, settling- and lock-time, and the impact of the voltage-controlled oscillator (VCO) phase noise on the performance of the time-mode filter are investigated. A sixth-order PLL is designed and fabricated on a printed circuit board and is used to validate the proposed synthesis method. In addition, an all-digital phase stimulus generation method well suited to a digital scan-based design-for-test (DFT) approach for testing the frequency response behavior of time-mode filters and other PLL-based designs is proposed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.900

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 communication0.0000.000
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 head0.024
GPT teacher head0.200
Teacher spread0.176 · 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 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

Citations17
Published2011
Admission routes1
Has abstractyes

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