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Record W2118418316 · doi:10.1109/iscas.2009.5117837

A low power current reused quadrature VCO for biomedical applications

2009· article· en· W2118418316 on OpenAlexaff
T. Khan, K. Raahemifar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPhase noiseVoltage-controlled oscillatordBcElectrical engineeringCMOSFrequency driftVoltageLow-power electronicsElectronic engineeringEngineeringPhysicsPower (physics)Power consumption

Abstract

fetched live from OpenAlex

This paper presents a low power current reusing quadrature voltage controlled oscillator for use in implantable electronics operating in the 402 MHz to 405 MHz medical implant communication service (MICS) frequency band. The oscillator was designed in IBM CMOS8RF 0.13 mum CMOS technology and simulated using Cadence IC5.141. The current reuse structure draws half the bias current as a conventional quadrature voltage controlled oscillator while exhibiting performance comparable to or exceeding that of previously published designs. Simulation results show that the oscillator phase noise is -127 dBc/Hz and consumes 1 mW of power from a 1 V supply. When the supply voltage is scaled to 0.65 V and biased for the same current consumption, the power consumption is reduced to 650 muW with phase noise of -111 dBc/Hz, which is almost 50% less power consumption when compared to oscillators in the same frequency band. The tuning range of the oscillator is 401.25 MHz to 407.5 MHz, enough to cover the MICS frequency band.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.247
Teacher spread0.238 · 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 designNot applicable
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

Citations15
Published2009
Admission routes1
Has abstractyes

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