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Record W2105982865 · doi:10.5539/mas.v7n12p34

Chopper Stabilized, Low-Power, Low-Noise, Front End Interface Circuit for Capacitive CMOS MEMS Sensor Applications

2013· article· en· W2105982865 on OpenAlexvenueno aff
N. Y. Sutri, John Ojur Dennis, Mohd Haris Md Khir, Muhammad Umer Mian, Tong Boon Tang

Bibliographic record

VenueModern Applied Science · 2013
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsnot available
Fundersnot available
KeywordsChopperCMOSCapacitive sensingElectrical engineeringCapacitanceCadenceNoise (video)Flicker noiseAmplifierMaterials scienceElectronic engineeringComputer scienceNoise figureVoltageEngineeringPhysics

Abstract

fetched live from OpenAlex

In this paper, a chopper stabilized fully differential CMOS pre-amplifier circuit is presented. The proposed circuit is designed for sub-atto Farad capacitive CMOS MEMS sensing applications. Chopper stabilization technique is employed to minimize flicker (1/f) noise and offsets in the circuit. The proposed circuit is designed using MIMOS 0.35 ?m AMS CMOS 3.3 V technology and simulation results from Cadence Virtuoso Spectre circuit simulator show that the proposed circuit is able to detect capacitance changes ranging from 0.0375 aF to 37.5 fF, attain an input inferred noise of 0.9 nV/ , gain of 18.1 dB at 3-dB frequency of 5.5 MHz with total power consumption of 0.33 mW.

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 score0.966
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.216
Teacher spread0.203 · 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

Citations7
Published2013
Admission routes1
Has abstractyes

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