The generation of correlated Rayleigh random variates by inverse discrete Fourier transform
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Bibliographic record
Abstract
A number of different algorithms are used for the generation of correlated Rayleigh random variates. This paper presents an analysis of the statistical properties of methods based on the inverse discrete Fourier transform (IDFT). A modification of the algorithm of Smith (1975) is presented, the new method requiring exactly one-half the number of IDPT operations and roughly two-thirds the computer memory of the original method. Evaluations of and comparisons between various variate generation methods using meaningful quantitative measures are believed to be lacking. New quantitative quality measures for random variate generation have been proposed that are, in particular, meaningful and useful for digital communication system simulation. This paper presents the application of these measures to the IDFT method and three other methods of correlated variate generation, comparing the algorithms in terms of the quality of the generated samples and the required computational effort.
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Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it