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Record W2142184012 · doi:10.1109/iccdcs.2002.1004017

CMOS analog sine function generator using lateral-PNP bipolar transistors

2003· article· en· W2142184012 on OpenAlexaboutno aff
Murilo Pilon Pessatti, Carlos Alberto dos Reis Filho

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsnot available
Fundersnot available
KeywordsCMOSBipolar junction transistorElectrical engineeringBiCMOSTotal harmonic distortionSine waveTransistorSineHarmonicsElectronic engineeringGenerator (circuit theory)PhysicsEngineeringVoltageMathematicsPower (physics)

Abstract

fetched live from OpenAlex

An implementation in CMOS technology of the ingenious analog sine function generator invented by Barrie Gilbert over two decades ago (Electron. Lett., vol. 13, pp. 506-508, 1977) is described in this paper. New in this circuit is the use of lateral-PNP bipolar transistors to build the core of the sine generator together with MOS transistors in the saturation region making up the rest of the circuit. Experimental results from prototypes of the circuit fabricated in 0.8 /spl mu/m CMOS technology showed that the accuracy of the produced sine is lower than that reported from implementations in bipolar and BiCMOS technologies (dos Reis Filho and Fruett, Proc. ICECS'97, 1997). The measured deviation from ideal sine over the (-/spl pi//2 to +/spl pi//2) range is less than 0.5%. Total harmonic distortion measured for a fundamental frequency at 20 kHz and the next four harmonics is approximately 1%. This circuit could be used in several applications, including the AC excitation of bridge-type sensors as a replacement for sinusoidal oscillators.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.191
Teacher spread0.173 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2003
Admission routes1
Has abstractyes

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