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Record W2131853781 · doi:10.1109/vetecf.2002.1040393

Combined CDMA and matrix pencil direction of arrival estimation

2003· article· en· W2131853781 on OpenAlexaff
Ching Lau, Raviraj Adve, Tapan K. Sarkar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDirection-of-Arrival Estimation Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDirection of arrivalAlgorithmCode division multiple accessMatrix pencilComputer scienceSnapshot (computer storage)Pencil (optics)Angle of arrivalMean squared errorComputational complexity theorySpeech recognitionMathematicsTelecommunicationsStatisticsPhysicsOptics

Abstract

fetched live from OpenAlex

This paper extends the low complexity, matrix pencil direction of arrival (DOA) estimation algorithm to the CDMA case. The CDMA processing gain is used to suppress interfering signals, allowing the matrix pencil to accurately estimate the DOA of the signal of interest. It is shown here that this CDMA/MP algorithm is able to estimate an angle of arrival (AOA) with a low mean square error using only a single snapshot. The popular Root-MUSIC algorithm which takes twice the execution time has a significantly higher MSE.

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 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 score0.849
Threshold uncertainty score0.320

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 science0.0000.000
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 head0.011
GPT teacher head0.265
Teacher spread0.254 · 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 teacher head, 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

Citations14
Published2003
Admission routes1
Has abstractyes

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