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Record W1604556734 · doi:10.1109/iscas.1999.777945

Dynamic CMOS noise immunity estimation in submicron regime

2003· article· en· W1604556734 on OpenAlexaff
Adnan Kabbani, A.J. Al-Khalili

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsConcordia University
Fundersnot available
KeywordsNoise immunityElectronic engineeringCMOSNoise (video)Computer scienceSpicePulse (music)Semiconductor device modelingControl theory (sociology)Electronic circuitElectrical engineeringEngineeringVoltage

Abstract

fetched live from OpenAlex

Noise may limit system performance, or it may push the system to malfunction. Hence a good system design has to take care of the noise problem. This paper addresses this issue and presents models to compute the noise immunity of dynamic CMOS circuits in submicron regime. Our models compute the maximum safe amplitude of a noise pulse in terms of the pulse duration as well as the circuit parameters. Also in these models the mobility degradation and velocity saturation have been taken in account. We have considered the cases where noise pulse is applied to one of the circuit inputs or the clock input. HSPICE simulations confirm the validity of these models.

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 score0.795
Threshold uncertainty score0.411

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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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

Citations4
Published2003
Admission routes1
Has abstractyes

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