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Record W2145229093 · doi:10.1109/iccdcs.2002.1004021

Ultra-low power VCOs - performance characteristics and modeling (invited)

2003· article· en· W2145229093 on OpenAlexafffund
M. Jamal Deen, M.H. Kazemeini, Sasan Naseh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsMcMaster University
FundersCMC Microsystems
KeywordsVoltage-controlled oscillatorCMOSVoltageElectrical engineeringTransistorPower consumptionPower (physics)Electronic engineeringLow voltageEngineeringComputer sciencePhysics

Abstract

fetched live from OpenAlex

The paper describes CMOS voltage controlled oscillators (VCOs) with ultra-low power capabilities. It presents a discussion of their performance characteristics and modeling using simple physics-based expressions. The oscillators have been designed in a commercial 0.18 /spl mu/m CMOS technology and the transistors in the VCOs operate from weak to strong inversion modes. They have been tested and found functional with supply voltages from 80 mV up to 1.8 V. Experimental results show that the VCO's power consumption is mainly dynamic for the whole range of supply voltages used and powers down to the nW regime has been achieved. A new and important feature of this VCO is the use of the substrate voltage as an additional control for the frequency tunability. In this way, a new VCO with two voltage controls for its operating frequency has been realized. The detailed experimental results and comparison to calculations are presented and discussed.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.180
Teacher spread0.168 · 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 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

Citations2
Published2003
Admission routes2
Has abstractyes

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