Bibliographic record
Abstract
Turbo product codes (TPC) are investigated for use in frequency-hopping spread-spectrum (FH-SS) communications in partial-band interference. Binary orthogonal FSK is employed with noncoherent envelope detection. The Fossorier-Lin (1995) algorithm of soft-decision decoding based on ordered statistics is employed for soft-in/soft-out decoder instead of Chase (1972) algorithm to reduce the required E/sub b//N/sub J/ for a given packet failure probability. Performance of TPC for FH-SS with and without memory is evaluated by simulation. A numerical method to calculate the upper bound on performance is also given. The results show that the low-complexity TPC has a similar performance to the high-complexity convolutional turbo codes (CTC) for FH-SS without memory. For FH-SS with memory, full interleaving is used for TPC to achieve a good performance at low duty factors of partial-band interference.
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How this classification was reachedexpand
Full frame distilled prediction
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".