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Record W2165238496 · doi:10.1109/icc.1993.397535

Joint source and channel coding using a non-linear receiver

2002· article· en· W2165238496 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
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsQAMAlgorithmEstimatorQuadrature amplitude modulationJoint (building)Computer scienceSIGNAL (programming language)Modulation (music)Channel (broadcasting)Coding (social sciences)MathematicsDecoding methodsTelecommunicationsBit error rateStatisticsAcoustics

Abstract

fetched live from OpenAlex

The joint optimization of the source and channel coders in a system consisting of a vector quantizer (VQ) whose output indices are mapped directly into points in the modulation signal space is considered. A decoder based on a nonlinear estimator is used to reconstruct the source signal. An iterative algorithm is introduced which jointly optimizes the VQ and the modulation signal set using as optimality criterion the minimum mean-square error (MSE) between the original and the reconstructed signals. It is shown that a jointly optimized system based on average channel characteristics significantly outperforms (by up to 5 dB) a reference system based on a VQ designed for the given source and a standard quadrature amplitude modulation (QAM) modulation signal set.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: Methods · Consensus signal: Methods
Teacher disagreement score0.949
Threshold uncertainty score0.357

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 communication0.0000.001
Open science0.0000.001
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 head0.072
GPT teacher head0.279
Teacher spread0.207 · 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

Citations65
Published2002
Admission routes1
Has abstractyes

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