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Record W2154674836

RF Noise Models of MOSFETs- A Review

2004· review· en· W2154674836 on OpenAlexaff
S. Asgaran, M. Jamal Deen

Bibliographic record

Venuenot available
Typereview
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNoise (video)Emphasis (telecommunications)MOSFETElectronic engineeringComputer scienceFlicker noiseEngineeringElectrical engineeringNoise figureTelecommunicationsCMOSTransistorArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

A thorough study of high frequency MOSFET noise compact modeling with emphasis on channel thermal noise modeling is presented. Although the modeling of MOSFET noise dates back to many years ago, the enhanced noise generated in short channel MOSFETs has made researchers revisit the problem to develop better models, especially in recent years. In this review, a detailed discussion of the most recent models published in the literature is provided. Each model is investigated in terms of physical and analytical aspects of the model, and some comments are made in each case. The induced gate noise, which is important in today’s high frequency applications, is also briefly reviewed at the end of this paper.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.837
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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)0.0010.000

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 head0.071
GPT teacher head0.314
Teacher spread0.243 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2004
Admission routes1
Has abstractyes

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