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Record W3105809257 · doi:10.22215/etd/2020-14170

Power Supply Induced Jitter Including the Ground Bounce and Transmission Media Effects

2020· dissertation· en· W3105809257 on OpenAlexaff
Ahsan Javaid

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsCarleton University
Fundersnot available
KeywordsJitterTransmission lineElectronic engineeringTransmission (telecommunications)Noise (video)Power (physics)Computer scienceElectric power transmissionSIGNAL (programming language)Signal integrityLine (geometry)Ground bounceEngineeringElectrical engineeringVoltageTelecommunicationsTransistorMathematics

Abstract

fetched live from OpenAlex

In this thesis, an efficient method for estimation of power supply induced jitter (PSIJ) in high-speed designs is presented. EMPSIJ Semi-analytical relations are developed based on small-signal noise analysis for quick estimation of PSIJ and one bit simulation of the large signal model. For this purpose, small-signal configuration of a voltage-mode driver circuit is considered to evaluate the differential output response. Also, an alternative and systematic approach is proposed based on MNA tridiagonal formulation and Thomas Algorithm for PSIJ analysis. It avoids re-derivation of the expressions in the case of any change in load conditions. Also, a novel closed-form model for transmission line type interconnects is developed relating the input and the output nodes of the transmission line which enables efficient PSIJ analysis in the presence of PCB traces. The proposed closed-form expression for transmission line type interconnects is also advanced to include the effect of load.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.878

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 integrity0.0000.001
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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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