Reconfigurable Microwave Filters Implemented Using Field Programmable Microwave Substrate
Bibliographic record
Abstract
This article presents novel designs of reconfigurable microwave filters based on the recently introduced concept of field programmable microwave substrate (FPMS). Using reconfigurable FPMS substrate, significant tuning freedom of the designed microwave filters can be achieved. It allows implementation of smart filter designs with tunable center frequencies, operational bandwidths, and filter orders. Moreover, different microwave filter types are also realizable on one FPMS board with simple dynamic control. As a proof-of-concept, design steps are described for three filter types, including waveguide bandpass filter, quarter-wave-coupled bandpass filter, and waveguide bandstop filter. A good match between the simulated and measured results is presented, showing good tuning range for the center frequency and bandwidth of the bandpass filters around 2 GHz. In addition, the reconfigurability of the design allows it to switch to bandstop filters, which is a complete change in topology from a single physical design. The merits of the proposed design are reflected in the realized bandpass filter, exhibiting center frequency tuning of more than 20% along with bandwidth variability spanning three times its minimum value. Finally, a significant size reduction compared with the designs using conventional technologies is also demonstrated. With its inherent flexibility, low cost, and high degree of integration, FPMS filtering is suited to a wide variety of RF applications.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".