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Record W1936384960 · doi:10.1002/cta.2049

Analysis and design of a high‐compliance ultra‐high output resistance current mirror employing positive shunt feedback

2014· article· en· W1936384960 on OpenAlexafffund
Mohammad Hossein Maghami, Amir M. Sodagar, Mohamad Sawan

Bibliographic record

VenueInternational Journal of Circuit Theory and Applications · 2014
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsPolytechnique Montréal
FundersCMC Microsystems
KeywordsShunt (medical)Compliance (psychology)Current mirrorCurrent (fluid)Control theory (sociology)Electrical engineeringComputer scienceReliability engineeringEngineeringElectronic engineeringPsychologyMedicineVoltageCardiologySocial psychologyTransistor

Abstract

fetched live from OpenAlex

SUMMARY This paper reports a novel high‐compliance, very accurate and ultra‐high output resistance current mirror. These features are achieved by employing a combination of negative and positive feedbacks in the proposed circuit. This makes the proposed current mirror unique in gathering ultra‐high output resistance, high compliance, and high accuracy ever demanded merits. The principle of operation of this structure is discussed, its main formulas are derived and its outstanding performance is verified by Cadence post‐layout simulations. Designed in the IBM 130‐nm standard CMOS process, the circuit consumes 230 × 110 µm 2 of silicon area. Post‐layout simulation results indicate that with a 3.3‐V power supply, output voltage compliance of 0.93V Supply is achieved at a maximum output current of 96 μA. Moreover, an extremely ultra‐high output resistance of 320 GΩ is achieved, which is one of the highest reported values of output resistance for current mirrors implemented using regular CMOS technology. The −3 dB upper cut‐off frequency of the proposed circuit is 100 MHz and the output/input current transfer error is 0.1%. The whole circuit, including bias circuitry, consumes 0.57 mW when delivering 96 μA to the load. Copyright © 2014 John Wiley & Sons, Ltd.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.426

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 head0.024
GPT teacher head0.275
Teacher spread0.251 · 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 designTheoretical or conceptual
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

Citations26
Published2014
Admission routes2
Has abstractyes

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