Constrained Inverse Near-Field Scattering Using High Resolution Wire Grid Models
Bibliographic record
Abstract
The microwave inverse problem is addressed using a wire grid model representation with capacitors loaded in parallel with resistors to respectively replace the permittivity and the conductivity of the device under test. A new approach is presented to embed the properties of isotropy and positiveness of the constitutive parameters without additional penalty terms or weighting parameters. An edge-preserving regularization technique is used to better estimate the discontinuities present in the device under test (DUT) and to decrease the sensitivity to noise during the reconstruction process. The optimization algorithm makes use of the conjugate gradient method to minimize the objective function. Synthetic data are used to assess the reconstruction speed of the new method. Simulation results show a five-fold reduction of the computation time compared to what had been presented previously. Experimental near-field measurements at 2.45 GHz on thin plate DUTs are used to assess the validity of the proposed reconstruction method. Satisfactory results are obtained and a spatial resolution of λ/20 is achieved.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".