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Record W2165468796 · doi:10.1109/ccece.2006.277668

On Selection of Optimum Signal Source Impedance for Inductively-Degenerated CMOS LNAS

2006· article· en· W2165468796 on OpenAlexafffundabout
Leonid Belostotski, J.W. Haslett

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaSmithsonian Astrophysical ObservatoryGovernment of AlbertaUniversity of Calgary
KeywordsCMOSElectronic engineeringAntenna (radio)Lossy compressionImpedance matchingNoise figureElectrical impedanceInductorSIGNAL (programming language)Computer scienceNoise (video)Electrical engineeringEngineeringTelecommunicationsAmplifier

Abstract

fetched live from OpenAlex

Noise figure optimization techniques for an inductively-degenerated CMOS LNA with a lossy gate inductor are presented. The techniques allow for integration of the LNA directly with a non -50 Omega antenna thus removing the need for a lossy matching circuitry. The LNA noise temperature is shown to reduce by a factor of 1 when non-standard signal source resistance is used. The LNA analyzed in this paper is targeted for the Canadian large adaptive reflector (CLAR)

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: none
Teacher disagreement score0.515
Threshold uncertainty score0.718

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 head0.010
GPT teacher head0.205
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

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

Citations4
Published2006
Admission routes3
Has abstractyes

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