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Record W2774249069 · doi:10.1109/tcsi.2017.2771141

Design of High-Order Type-II Delay-Locked Loops With a Fast-Settling-Zero-Overshoot Step Response and Large Jitter-Rejection Capabilities

2017· article· en· W2774249069 on OpenAlexafffund
Yan Li, Gordon W. Roberts

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOvershoot (microwave communication)Phase marginJitterDelay-locked loopTransfer functionControl theory (sociology)Settling timeFilter (signal processing)Step responseComputer scienceRealization (probability)Electronic engineeringPhase-locked loopStability (learning theory)CMOSEngineeringControl engineeringAmplifierMathematicsOperational amplifier

Abstract

fetched live from OpenAlex

In this paper, a design method for high-order delay-lock loops (DLLs) is presented and verified through simulations and physical experiments. The general approach is based on selecting the closed-loop transfer function of the DLL, together with identifying the coefficients of the phase-detector and voltage-controlled delay line, and subsequently, solving for parameters of the loop filter of the DLL. Past DLL design approaches relied more on establishing a desired phase margin requirement than attempting to establish a desired input-output behavior. This limited the realization of DLLs to second order; largely a result of the complicated mathematics that arise. As the method proposed in this paper is based on selecting a desired closed-loop transfer function, the issues of stability or phase margin never come to the forefront. This paper will show how a DLL can be designed to achieve a fast-settling-zero-overshoot step response with large jitter-rejection capabilities. The method is simple and easy to execute. No optimization or iteration is necessary. The method is similar to the methods used to design active-RC filter circuits. A fully programmable experimental prototype involving a custom IC implemented in a 130-nm IBM CMOS process was constructed. DLLs with orders ranging from second to eighth will be investigated.

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 score0.514
Threshold uncertainty score0.817

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 studies0.0010.000
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 head0.015
GPT teacher head0.218
Teacher spread0.203 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

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