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Record W2100010696 · doi:10.1002/cta.792

A 5‐GHz energy‐efficient tunable pulse generator for ultra‐wideband applications using a variable attenuator for pulse shaping

2011· article· en· W2100010696 on OpenAlexafffund
Ahmed M. El‐Gabaly, Carlos E. Saavedra

Bibliographic record

VenueInternational Journal of Circuit Theory and Applications · 2011
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsQueen's University
FundersCMC Microsystems
KeywordsCMOSAttenuator (electronics)Pulse generatorElectrical engineeringImpulse generatorSignal edgeUltra-widebandDuty cyclePulse durationEnvelope detectorWidebandCapacitorVoltageElectronic engineeringMaterials scienceEngineeringPhysicsOpticsAttenuation

Abstract

fetched live from OpenAlex

SUMMARY A new energy‐efficient tunable pulse generator is presented in this paper using 0.13‐µm CMOS technology for short‐range high‐data‐rate 3.1–10.6 GHz ultra‐wideband applications. A ring oscillator consisting of current‐starved CMOS inverters is quickly switched on and off for the duration of the pulse, and the amplitude envelope is shaped with a variable passive CMOS attenuator. The variable passive attenuator is controlled using an impulse that is created by a low‐power glitch generator (CMOS NOR gate). The glitch generator combines the falling edge of the clock and its delayed inverse, allowing the duration of the impulse to be changed over a wide range (500–900 ps) by varying the delay between the edges. The pulses generated with this technique can provide a sharp frequency roll off with high out‐of‐band rejection to help meet the Federal Communications Commission mask. The entire circuit operates in switched mode with a low average power consumption of less than 3.8 mW at 910 MHz pulse repetition frequency or below 4.2 pJ of energy per pulse. It occupies a total area of 725 × 600 µm 2 including bonding pads and decoupling capacitors, and the active circuit area is only 360 × 200 µm 2 . Copyright © 2011 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.033
GPT teacher head0.255
Teacher spread0.223 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations4
Published2011
Admission routes2
Has abstractyes

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