Continuously Tunable Fractional Hilbert Transformer by Using a Single $\pi$-Phase Shifted FBG
Bibliographic record
Abstract
A continuously tunable fractional Hilbert transformer (FHT) using a π-phase shifted fiber Bragg grating ( π-PSFBG) is proposed and experimentally demonstrated. An FHT has an output that is a weighted sum of the original input signal and its classical Hilbert-transformed signal. The classical Hilbert transform is implemented using a π-PSFBG. The output from the classical HT and the original input signal are controlled to be orthogonally polarized. The combination of the two signals at a polarizer would generate a weighted sum with the weighting coefficients determined by the angle between the principle axis of the polarizer and the polarization direction of the original input signal. A π-PSFBG is fabricated. The performance of the π-PSFBG as a classical HT is evaluated. The incorporation of the π-PSFBG into the proposed system to implement an FHT is studied. A continuously tunable FHT with a tunable fractional order of ρ = 0.7, 0.86, 0.92, 1, 1.06, 1.17, and 1.24 to perform Hilbert transformation of a Gaussian pulse with a temporal width of 80 ps is experimentally demonstrated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".