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Record W1993279477 · doi:10.1155/2007/45269

Flexible Architecture of Ultra-Low-Power Current-Mode Interleaved Successive Approximation Analog-to-Digital Converter for Wireless Sensor Networks

2007· article· en· W1993279477 on OpenAlex

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

VenueVLSI design · 2007
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCMOSAnalog-to-digital converterElectronic engineeringComputer sciencePower (physics)DissipationSampling (signal processing)Figure of meritElectrical engineeringSuccessive approximation ADCVoltageCapacitorEngineeringPhysics

Abstract

fetched live from OpenAlex

A novel 8-bit current mode interleaved successive approximation (SAR) analog-digital converter (ADC) has been proposed. The proposed converter architecture is very flexible. Using two control DC voltages and one reference current, the converter can be tuned to work with different sampling rates, number of bits of resolution, and power consumption levels. Due to its very low-power consumption and flexibility, the converter is particularly suitable for application in wireless sensor networks. Compared to other solutions presented in the literature, the proposed converter achieves very high figure of merit (FOM) value due to numerous low-power circuit innovations utilized in its design. The circuit has been implemented in CMOS 0.18 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>μ</mml:mi></mml:math>m technology. Minimum energy consumption has been found to be in a 25–250 kS/s range (for clock sampling frequency in a 200 kHz--2 MHz range) for a single SAR section with the corresponding power dissipation varying from 220 nW to 560 nW for 0.55 V power supply.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
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)0.0000.000

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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