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Record W4249292489 · doi:10.1002/9781118684207.ch11

Digital Signal Processing

2014· other· en· W4249292489 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
Typeother
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDigital signal processingPolarization mode dispersionNonlinear systemDispersion (optics)Signal processingElectronic engineeringModal dispersionFiber-optic communicationComputer sciencePolarization (electrochemistry)SIGNAL (programming language)OpticsOptical fiberPhysicsTelecommunicationsDispersion-shifted fiberEngineeringFiber optic sensor

Abstract

fetched live from OpenAlex

The key component that revived coherent fiber communications in the mid-2000 was high-speed digital signal processing (DSP). With the advances in high-speed DSP, phase alignment and polarization management can be done in the electrical domain. Linear impairments such as chromatic dispersion (CD) and polarization mode dispersion can be compensated using equalizers. It is also possible to compensate for the interplay between dispersion and nonlinearity by using digital back propagation (DBP), in which the nonlinear Schrödinger equation is solved for a virtual fiber whose signs of dispersion, loss, and nonlinear coefficients are opposite to those of the transmission fiber.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.356
Threshold uncertainty score1.000

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)0.0010.001

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 head0.005
GPT teacher head0.182
Teacher spread0.177 · 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

Citations14
Published2014
Admission routes1
Has abstractyes

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