Design of quadrature mirror-image filter banks for low-power applications
Why this work is in the frame
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Bibliographic record
Abstract
A method for the design of quadrature mirror-image filter QMF banks for low-power applications based on the algorithm of Chen and Lee (1992) is proposed. The method entails designing a sequence of cascaded filter sections such that any number of consecutive sections starting with the first one constitute an optimal design for a given set of specifications for the filter bank. The method includes modifications that allow for the increase in vanishing moments with the increase in the number of filter sections and it can incorporate techniques that facilitate control over the stopband attenuation or enable the design of low-reconstruction delay QMF banks. Using a simple adaptive mechanism, the input and output signals are used to determine the minimum number of sections that should be used in order to provide a desired performance. By turning off unrequired sections, power and computational complexity can be minimized.
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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 | 0.001 |
| 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