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Record W4392603861 · doi:10.1002/9781394205318.ch6

Photonic Generation of Ultra‐Wideband Signals

2024· other· en· W4392603861 on OpenAlexaff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhotonicsWidebandOptoelectronicsComputer sciencePhysicsOptics

Abstract

fetched live from OpenAlex

Ultra-wideband (UWB) has been considered a solution for short-range high-throughput wireless communications and sensor networks thanks to their intrinsic properties, such as the immunity to multipath fading, extremely short time duration, carrier-free, low duty cycle, wide bandwidth, and low power consumption. This chapter discusses techniques to generate UWB pulses in the optical domain. These techniques are classified into three categories: UWB pulse generation based on phase-modulation to intensity-modulation (PM-IM) conversion. The PM-IM conversion can be implemented in the optical domain by using either a dispersive device or an optical frequency discriminator. UWB pulse generation using a photonic microwave delay-line filter. A photonic microwave delay-line filter with incoherent detection can usually have positive coefficients only. The chapter discusses two methods to generate a negative coefficient. First, a negative coefficient is generated based on XGM in an SOA. In the second method, a PolM is used.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.122
Threshold uncertainty score0.997

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)0.0040.001

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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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