A new miniature uniplanar lowpass filter using series resonators
Bibliographic record
Abstract
A new variant of miniature uniplanar lowpass filter suitable for use as a building block for communication systems is investigated. A combination of CPW series resonators and low impedance line sections is used to form this lowpass filter. This is made possible by the potential power offered by the uniplanar technology in terms of the wide range of flexibility and scope for innovation. Furthermore, this alternative structure removes a number of limitations inherent to the conventional configuration. Compared to ladder type built from the cascade of alternate high and low impedance line sections, several advantages are pointed out: very wide stopband with low number of elements (no spurious responses up to 25 GHz), high cutoff rates, low insertion loss, lower radiation loss, high compactness (a significant 35% reduction of the circuit area when compared to ladder type) and additional degrees of freedom by the inclusion of the series CPW series resonators in the filter design. However, to fully benefit from these resonators, it is necessary to have reliable models of each constitutive element of the lowpass filter. It has been shown that the relative flexibility of the space domain integral equation method makes it an attractive tool for the analysis and design of these complex circuits. A principle of achieving these high-quality circuits is described and also confirmed by experimental and theoretical results, which are in good agreement up to 40 GHz. The combination of a series resonators with low impedance line sections gives a new powerful technique for the design of miniature lowpass suitable for monolithic millimetric integrated circuits.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 0.001 |
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".