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Record W2001192065 · doi:10.1117/12.628577

Pulse distortion and power penalty induced by sinusoidal amplitude and phase response ripples for Gaussian pulses

2005· article· en· W2001192065 on OpenAlexaff
Ning Cheng, John C. Cartledge

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsQueen's University
Fundersnot available
KeywordsDistortion (music)Phase distortionAmplitudeAmplitude distortionOpticsChirpRippleSIGNAL (programming language)PhysicsPhase (matter)Pulse-amplitude modulationPulse (music)Power (physics)Pulse compressionWavelengthGaussianPulse shapingComputer scienceNonlinear distortionTelecommunicationsLaserAmplifierOptoelectronics

Abstract

fetched live from OpenAlex

Wavelength-selective optical components used in WDM optical communication systems often exhibit a transfer function with amplitude and phase ripples. These ripples can lead to signal distortion and performance degradation. The pulse distortion induced by sinusoidal amplitude and phase response ripples is derived for Gaussian pulses, and concise results are presented for the power penalty in system performance. The analysis shows that the amplitude and phase response ripples have a similar impact on the transmitted signal, and the power penalty induced by these ripples depends on the chirp and pulse width of the transmitted signal. The combined effect of the characteristics of the transmitted signal and the ripple parameters on the system performance is discussed in detail. Numerical simulations show a good agreement with the theoretical analysis.

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)0.002
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.248
Teacher spread0.237 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced Fiber Optic SensorsFrench-language works237,207