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Record W4226227872 · doi:10.1109/tvlsi.2022.3155052

A 4th-Order 4-Bit Continuous-Time ΔΣ ADC Based on Active–Passive Integrators With a Resistance Feedback DAC

2022· article· en· W4226227872 on OpenAlexafffund
Ningcheng Gaoding, Jean‐François Bousquet

Bibliographic record

VenueIEEE Transactions on Very Large Scale Integration (VLSI) Systems · 2022
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsIntegratorEffective number of bitsElectronic engineeringDelta-sigma modulationNoise shapingOperational amplifierDigital biquad filterSuccessive approximation ADCBandwidth (computing)Figure of meritAmplifierComputer scienceEngineeringElectrical engineeringCapacitorCMOSLow-pass filterTelecommunications

Abstract

fetched live from OpenAlex

This article reports a fourth-order continuous-time (CT) delta–sigma modulator (DSM) that features a single-amplifier biquad, a passive integrator, and an active integrator. This simplifies the circuit to only two op-amps in comparison to four power-hungry op-amps used in a conventional fourth-order DSM. In addition to improving the power consumption, the proposed design also has more relaxed requirements for the gain–bandwidth product and the loop gain. A 4-bit flash analog-to-digital converter (ADC) and two feedback digital-to-analog converters (DACs) are employed in this design to implement a fully integrated CT DSM. By incorporating the passive network in front of the last active integrator, this design gives a better attenuation at high frequency, which decreases the possibility of instability caused by out-of-band high-frequency signals. The proposed design has a measured bandwidth of 2 MHz with a power consumption of only around 3 mW. The effective number of bits (ENOB) of the proposed CT-DSM is approximately 12.7 bits with a peak signal-to-noise and distortion ratio (SNDR) around 78 dB, and it also exhibits a good Schreier figure of merit on the order of 166 dB compared to the existing state of the art.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.183
Teacher spread0.178 · 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 designSimulation or modeling
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

Citations8
Published2022
Admission routes2
Has abstractyes

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