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Record W2014265151 · doi:10.1109/icuwb.2015.7324465

Integrated UWB Transmitter and Antenna Design for Interfacing High-Density Brain Microprobes

2015· article· en· W2014265151 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTransmitterElectronic engineeringPhase-shift keyingAntenna (radio)Transmission (telecommunications)Computer scienceModulation (music)InterfacingCMOSElectrical engineeringAmplitude-shift keyingEngineeringTelecommunicationsBit error ratePhysicsChannel (broadcasting)Computer hardwareAcoustics

Abstract

fetched live from OpenAlex

This paper presents and compares two transmitter topologies (TX1 and TX2) using different modulation schemes to provide high data rate in high-density neural recording systems. Both transmitters use IR-UWB implemented based on an edge combining approach. TX2, which is using an improved topology, consumes less power and uses less area than TX1, while supporting the same data rate. The power consumption is also reduced by 35% at 500 Mbps in TX2. Both transmitters employ pulse shaping within the 3.1 and 7 GHz subband of the unregulated ultra-wide band to mitigate high transmission loss of the propagated EM waves above 7 GHz inside biological tissues. An implantable antenna and an external antenna are designed for utilization as TX and RX antennas in this application, respectively. Both transmitters have been fully integrated into a standard TSMC 0.18-μm CMOS technology and provide high data transmission rate above 500 Mbps. TX1 supports OOK and binary phase shift keying (BPSK) modulations, while TX2 supports only OOK modulation.

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.

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 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 score0.781
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.024
GPT teacher head0.209
Teacher spread0.184 · 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

Quick stats

Citations11
Published2015
Admission routes1
Has abstractyes

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