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Record W2080150587 · doi:10.1002/ett.992

Generation of multiple Rayleigh fading sequences with specified cross‐correlations

2004· article· en· W2080150587 on OpenAlexaff
Norman C. Beaulieu, Maria Luisa Merani

Bibliographic record

VenueEuropean Transactions on Telecommunications · 2004
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRayleigh fadingFadingToeplitz matrixAlgorithmComputational complexity theoryEnvelope (radar)MathematicsRayleigh scatteringBlock (permutation group theory)Computer scienceTelecommunicationsCombinatoricsPhysicsOpticsDecoding methodsPure mathematics

Abstract

fetched live from OpenAlex

Abstract A recent technique for generating two spatially correlated Rayleigh fading envelope sequences is generalized to give an efficient method for the generation of multiple correlated Rayleigh fading sequences. By coloring the quadrature components of the Rayleigh sequences, any desired envelope correlations can be realized for an arbitrary number of diversity branches. The computational complexity of the new method is compared to the computational complexity of a direct method. It is shown that properly utilizing the underlying block Toeplitz structure of the correlation matrix gives computational savings over the direct method. Copyright © 2004 AEI.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.089
GPT teacher head0.302
Teacher spread0.212 · 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

Citations16
Published2004
Admission routes1
Has abstractyes

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