Non-standard CAN Network Topologies Verification at High Speed Transmission Rate using VHDL-AMS
Bibliographic record
Abstract
This paper considers the verification of non-standard CAN network topologies of the physical layer at high speed transmission rate (500.0Kbps and 1.0Mbps). These network topologies including single star, multiple stars, and hybrid topologies (multiple stars in combination with linear bus or with ring topology) are simulated by using behavior modeling language (VHDL-AMS) in comparison to measurement. Throughout the verification process, CAN transceiver behavioral model together with other CAN physical layer simulation components have been proved to be very accurate. The modeling of measurement environment of the CAN network is discussed, showing how to get the measurement and simulation results well matched. This demonstrates that the simulation solution is reliable, which is highly desired and very important for the verification requirement in CAN physical layer design. Last but not least, with the developed CAN measurement system, application layer is also proved working properly when implementing different non-standard topologies at high speed transmission rate.
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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 | 0.001 | 0.003 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".