A novel finite-wordlength particle swarm optimization technique for FRM IIR digital filters
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Bibliographic record
Abstract
A novel technique is presented for finite-wordlength (FW) particle swarm optimization (PSO) of BIBO stable FRM digital filters incorporating bilinear-LDI IIR interpolation subfilters. A novel LUT scheme is developed to ensure that the FWPSO automatically searches over permissible FW multiplier coefficient values only in the course of optimization. The salient feature of the proposed LUT scheme is that unlike the conventional PSO, there is no need to limit the search space in the course of optimization to prevent going over the boundaries of the search space. This is achieved by introducing barren layers in the LUTs. The usefulness of the proposed FWPSO is illustrated through its application to the design and simultaneous magnitude and group-delay optimization of a lowpass IIR-based FRM digital filter.
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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 | 0.002 |
| 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