MétaCan
Menu
Back to cohort
Record W2151990255 · doi:10.1109/wcnc.2011.5779393

Novel representations for the multivariate non-central chi-square distribution with constant correlation and applications

2011· article· en· W2151990255 on OpenAlexaff
Kasun T. Hemachandra, Norman C. Beaulieu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCumulative distribution functionConstant (computer programming)Probability density functionMathematicsJoint probability distributionComputer scienceFunction (biology)Applied mathematicsSquare (algebra)Probability distributionDiscrete mathematicsStatistics

Abstract

fetched live from OpenAlex

Novel representations for the multivariate probability density function (PDF) and cumulative distribution function (CDF) of the equi-correlated non-central chi-square (χ2) distribution are derived. The new representations are given as single integral solutions in terms of well known mathematical functions which are available in common mathematical software packages. The advantage of the new representations is that only a single integral computation is needed to evaluate the PDF and CDF for an arbitrary number of dimensions. The new representations are used to numerically evaluate the outage probability of a single user multiple input multiple output system with receiver antenna selection diversity, operating in correlated Rician fading channels. The well known constant (equal) correlation model, which is considered to be a useful model for a closely placed set of antennas, is used for the analysis in this paper. A novel single-integral representation for the joint characteristic function of the equi-correlated non-central χ2distribution is also given.

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)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.024
GPT teacher head0.256
Teacher spread0.233 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations6
Published2011
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Wireless Communication TechniquesFrench-language works237,207