A comparative study of FFT-summation and polyphase-FFT CFAR detectors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A priori knowledge of the signal channelization and bandwidth can be used to design efficient signal processing strategies for the detection of narrowband signals. Approaches based on digital filter banks are particularly attractive since a large number of channels can be searched in parallel. A simple and computationally efficient idea involves the use of an FFT that has been designed so that each FFT bin corresponds to a channel. The performance limitations of the FFT detector can be resolved by processing longer signal data records using the polyphase-FFT. An alternative idea for improving detection performance involves increasing the FFT length so that the signal power in each channel is obtained by summing the power computed for two or more FFT bins. This FFT-summation detector offers greater flexibility in the allowable channelization schemes and can provide performance characteristics similar to those of the polyphase-FFT detector.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it