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Record W3011653750 · doi:10.1109/icm48031.2019.9021776

Investigating the Developments on the Frequency Compensation Techniques of the Two-Stage OTAs - A Brief Guide and Updated Review -

2019· article· en· W3011653750 on OpenAlexaff
Mahmood A. Mohammed, Gordon W. Roberts

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsMcGill University
Fundersnot available
KeywordsTransconductanceCompensation (psychology)AmplifierElectronic engineeringWork (physics)Operational amplifierComputer scienceEngineeringFrequency compensationStage (stratigraphy)Electrical engineeringVoltageCMOSMechanical engineering

Abstract

fetched live from OpenAlex

Frequency compensation techniques (FCTs) of the two-stage Operational Transconductance Amplifiers (OTAs) are of critical importance in analog design. They are considered essential for all other FCTs of multi-stage OTAs. In this work, the developments of the major FCTs of the two-stage OTAs are investigated. This brief investigation includes tracking the original work on each major FCT. The description of these original works is discussed along with the possibility of improvements on each major technique, as some of these techniques have not been fully developed. Also, this work shows the gradual developments of each major FCT, which might help predicting the future of these FCTs. This work can be used as a guide for the design engineers as well as the universities teaching graduate level advanced electronics and OTAs/Op-amps courses.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.021
GPT teacher head0.239
Teacher spread0.218 · 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 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

Citations7
Published2019
Admission routes1
Has abstractyes

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