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Record W1486336998 · doi:10.1109/iscas.2005.1464991

Novel μ-Power Log-Domain Integrators

2005· article· en· W1486336998 on OpenAlexaff
W. Aly-Mekawi, E.I. El-Masry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsDalhousie University
Fundersnot available
KeywordsIntegratorTotal harmonic distortionChebyshev filterPMOS logicBiasingOp amp integratorCMOSFilter (signal processing)Control theory (sociology)VoltagePassive integrator circuitElectronic engineeringCapacitorPhysicsOperational amplifierTopology (electrical circuits)Computer scienceElectrical engineeringEngineeringRC circuitAmplifierTransistor

Abstract

fetched live from OpenAlex

This paper introduces novel CMOS bulk driven log-domain integrators using the CMOSP 0.18-/spl mu/m process. The proposed design technique is based on the incomplete translinear loop (ITL). The integrators' unique function is to cancel the slope factor n, which in turn results in: (1) reducing the biasing current, (2) reducing the power consumption, and (3) better time constant tenability. As an application, the integrators are used to design a 4th-order Chebyshev low-pass filter that can be tuned from 100 Hz to 10 MHz. The filter is biased by 300 nA, which corresponds to a tuned cut-off frequency of 1 MHz. The supply voltage is 1.8 V and the dynamic range is 50 dB for a PMOS prototype at THD 1%. The power consumption is 0.945 /spl mu/W per pole.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.192
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2005
Admission routes1
Has abstractyes

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