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Record W2065716530 · doi:10.1049/ip-com:20050440

Spectra of multimode coded signals

2006· article· en· W2065716530 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

VenueIEE Proceedings - Communications · 2006
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEncoderCode wordRandomnessComputer scienceAlgorithmCoding (social sciences)Spectral densityMulti-mode optical fiberTheoretical computer scienceMathematicsDecoding methodsTelecommunicationsStatistics

Abstract

fetched live from OpenAlex

Multimode coding is an efficient block coding technique that introduces control over sequence statistics by generating a number of alternatives to represent the source word in each encoding interval and then selecting the word that best meets the system constraints. The power spectral density (PSD) of the encoded signal is of particular interest with these codes. Standard techniques for evaluation of the PSD of block coded sequences cannot be directly applied to a wide variety of multimode codes in which encoder state probabilities do not reach a stationary distribution, or in which codeword selection is random when two or more alternatives satisfy system constraints. In the paper standard spectral analysis techniques are extended to enable evaluation of the PSD of signals generated by multimode codes with these characteristics. It is demonstrated that randomness in selection can result in suppression of discrete components in the encoded signal that may otherwise arise under adverse conditions.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.507
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0040.001
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 head0.029
GPT teacher head0.303
Teacher spread0.274 · 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