Analysis of the coefficients of generalized bilinear transformation in the design of 2-D band-pass and band-stop filters and an application in image processing
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Bibliographic record
Abstract
Due to rapid progress in the field of speech and image processing, there is a greater need of a digital filter which possesses variable magnitude characteristics; one such filter is proposed in this paper. The proposed 2-D band-pass and band-elimination filters are designed from a 1-D low-pass Butterworth filter by applying a low-pass to band-pass and low-pass to band-stop transformations respectively. The resulting structure is converted to 2-D analog filter by making the series arm having impedances in s/sub 1/-domain and the shunt-arm impedances in the s/sub 2/-domain. The filters so obtained are digitized using the generalized bilinear transformations, thereby giving eight variables to be adjusted, giving a large number of possible magnitude characteristics. It is further shown how these filters can be utilized in reducing the noise content in images.
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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 | 0.001 |
| 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