Design and Development of an Inexpensive Sub-Nanosecond Gaussian Pulse Transmitter
Bibliographic record
Abstract
A design of a hybrid Gaussian pulse transmitter using a transistor-based pulse generator and two pulse-shaping networks, a shorted stub delay circuit and a 90° hybrid coupler, is presented. A transistor-based pulse generator drives the pulse-forming network to achieve a sub-nanosecond pulsewidth. The shorted stub delay line was modified to optimize the frequency response and phase linearity. The transistor-based pulse generator is an inexpensive way of producing a square pulse of sharp rise time; this design achieved 280-ps rise time. A Schottky diode was used to eliminate the negative part of the output pulse as well as to reduce the ringing. Multiple simulations and measurements were performed to study the circuit behavior. The measurement results demonstrated a pulsewidth as sharp as 153 ps with 0.83-V amplitude and a low ringing on the order of 10%. The Gaussian monopulse was obtained by feeding the Gaussian pulse to a broadband 90° hybrid, which acts as a differentiator in the time domain. The pulse has a width on the order of 100 ps. The transmitter circuit was completed by connecting the monopulse circuit with an antenna. The measured radiated pulse in the far field of the transmitter is a second derivative Gaussian pulse with 85 ps of pulsewidth.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".