Design of two-dimensional digital filters using integer coefficient 2-D all-pass filters
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Bibliographic record
Abstract
Presented here is a method for the design of 2-D causal quarter-plane recursive digital filters with integer coefficients and arbitrary magnitude characteristics, by using all-pass building blocks. It is shown that in general, cascade of sum or difference of two 2-D all-pass filters with appropriate delay elements are required to guarantee the arbitrary shape of the cutoff boundary of the desired filters. To design a 2-D filter satisfying given specifications the binary parameters of the cascaded all-pass structure are adapted from the given table, and the coefficients of the 2-D all-pass filters are obtained via an iterative technique by using a nonlinear optimization method coupled with discretization and re-optimization method. An example is given to illustrate the usefulness of the proposed technique.
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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 | 0.001 | 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