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On the von Mises Phase Model for the FFT-Based Two-Channel Digital Interferometer

2025· article· W7127337107 on OpenAlex
Sichun Wang, W. A. Read

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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
Language
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsDefence Research and Development Canada
Fundersnot available
Keywordsvon Mises yield criterionvon Mises distributionInterferometryPhase (matter)Distribution (mathematics)Digital computerInverse trigonometric functions

Abstract

fetched live from OpenAlex

In scientific literature on geolocation applications, it has been demonstrated by theoretical numerical techniques that the von Mises distribution can be effectively used to model phase measurements for the frequency-domain FFTbased two-channel digital interferometer if there is no input data overlap. For the more difficult case of overlapped input data, no such systematic theoretical treatment has been published. In this paper, we fill this literature gap and, using a combination of theoretical analysis and computer simulations, we show that the same conclusion also holds true in the case of overlapped input data. Thus the von Mises distribution can be always used as an effective alternative phase model for FFT-based two-channel digital interferometers no matter whether there is input data overlap or not.

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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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.997

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 studies0.0010.000
Scholarly communication0.0040.001
Open science0.0020.000
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 head0.082
GPT teacher head0.341
Teacher spread0.259 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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