Application of frequency-response masking technique to the design of a novel modified-DFT filter bank
Why this work is in the frame
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Bibliographic record
Abstract
Modified-DFT (MDFT) filter banks permit subchannels with linear phase characteristics, and provide high degrees of computational efficiency. However, in MDFT filter banks with subchannels exhibiting narrow transition-bandwidths, the length of the prototype filter becomes prohibitively long, reducing the computational efficiency. It is well known that the frequency-response masking (FRM) technique provides an attractive technique for the realization of digital filters with very narrow transition-bandwidths. In this paper, the FRM digital filter design technique is exploited and applied to the design of a novel cascaded MDFT filter bank realizing selective subchannels with very narrow transition-bandwidths. An application example is given to illustrate the design of the proposed MDFT filter bank. It is shown that the resulting filter bank entails substantially less computational complexity compared to the conventional MDFT filter banks
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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 | 0.001 | 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 | 0.001 | 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