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Record W1977411384 · doi:10.1109/tcsii.2013.2281891

An Interface Circuit With Wide Dynamic Range for Differential Capacitive Sensing Applications

2013· article· en· W1977411384 on OpenAlexaff
Fatemeh Aezinia, Behraad Bahreyni

Bibliographic record

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCapacitive sensingDynamic rangeCMOSCapacitanceBandwidth (computing)Electronic engineeringChipWide dynamic rangeElectronic circuitDemodulationSIGNAL (programming language)Electrical engineeringComputer scienceEngineeringPhysicsTelecommunications

Abstract

fetched live from OpenAlex

An interface circuit for differential capacitive sensing applications with tunable dynamic range is presented. Capacitive microsensors are ubiquitously employed in many applications pertaining to all aspects of modern life. The proposed circuit requires a small chip area and offers a good signal-to-noise ratio as well as adjustable sensitivity and dynamic range. Reference signals are produced on chip and used for the synchronous demodulation of current signals through a differential capacitive sensor. In addition to the normal open-loop operation mode of the circuit, it can be operated within a novel closed-loop configuration in order to extend its dynamic range. The circuit was designed and fabricated in a standard 0.35-μm CMOS technology from Austriamicrosystems. Experimental and simulation results are presented and discussed. The circuit is capable of resolving 0.4 fF of variation in capacitance with a 50-kHz measurement bandwidth. Reducing the bandwidth to 1 kHz for signal frequencies around 10 kHz increases the dynamic range of the closed-loop circuit to 99 and 110 dB for open-loop and closed-loop circuits, respectively.

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 categoriesMeta-epidemiology (narrow)
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 score0.822
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 communication0.0000.001
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 head0.011
GPT teacher head0.223
Teacher spread0.212 · 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.

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

Citations20
Published2013
Admission routes1
Has abstractyes

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