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Record W2143644977 · doi:10.1109/iscas.2011.5937489

An ultra-low-power SAR ADC with an area-efficient DAC architecture

2011· article· en· W2143644977 on OpenAlex
Pouya Kamalinejad, Shahriar Mirabbasi, Victor C. M. Leung

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEffective number of bitsSuccessive approximation ADCCapacitorCMOSElectronic engineeringPower (physics)Analog-to-digital converterLow-power electronicsComputer scienceUltra low powerElectrical engineeringPower consumptionVoltageEngineeringPhysics

Abstract

fetched live from OpenAlex

An ultra-low-power area-efficient 8-bit successive approximation register (SAR) analog-to-digital converter (ADC) is presented. To achieve ultra-low-power performance a DAC architecture is proposed that employs two rail-to-rail low-power unity-gain buffers and only 4 minimum-size capacitors instead of the conventional binary-weighted capacitor array. Thereby, power consumption and area are drastically reduced by virtue of lower switching activity and smaller size capacitor array. The proposed 8-bit SAR ADC is designed and simulated in a 0.13μm CMOS process. Simulation results show that for a 2.4 kHz (12.4 kHz) input signal while sampling at 25 kHz, the ADC achieves an ENOB of 7.9 (7.8), consumes 290 nW (350 nW) form a 0.8 V analog supply and a 0.6 V digital supply, and achieves a FoM of 48 fj/conversion-step (62 fj/conversion-step).

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.583
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.185
Teacher spread0.172 · 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

Quick stats

Citations22
Published2011
Admission routes1
Has abstractyes

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