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Record W2147065678 · doi:10.1109/82.974786

RF noise characterization of MOS devices for LNA design using a physical-based quasi-3-D approach

2001· article· en· W2147065678 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing · 2001
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNoise (video)NMOS logicElectronic engineeringMOSFETNoise temperatureNoise generatorMicrowaveFlicker noiseTransistorNoise figureNoise measurementY-factorElectrical engineeringEffective input noise temperaturePhysicsComputer scienceAcousticsEngineeringPhase noiseNoise reductionCMOSTelecommunicationsAmplifier

Abstract

fetched live from OpenAlex

A quasi-3-D method for microwave noise simulation of MOSFET is presented in this paper. This method inherently takes into account all the microscopic noise sources within the transistor at microwave frequencies. It is realized by properly transforming the 2-D noise sources to 3-D equivalent noise sources. The 2-D noise sources and their correlation term are calculated in the framework of a PDE based 2-D device simulator. Based on 3-D equivalent noise network, the four noise parameters F/sub min/, R/sub n/, R/sub opt/, and X/sub opt/ which are critical for low noise device design are calculated. A 0.5 -/spl mu/m LDD nMOS transistor was simulated and the simulation results were compared to measurement data. The functional behavior of the four noise parameters at microwave frequency with bias and layout parameters is illustrated. An example for designing a low noise MOSFET for RF application is provided.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.039
GPT teacher head0.234
Teacher spread0.195 · 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