Adjoint network of periodically switched linear circuits with applications to noise analysis
Bibliographic record
Abstract
In this paper, Tellegen's theorem for multiphase periodically switched linear (PSL) circuits in phasor domain and the adjoint network of PSL circuits are developed. Two new theorems are introduced and theoretical proofs are given. The first theorem, called the transfer function theorem, gives an efficient way to calculate the transfer functions from multiple inputs to a single output of PSL circuits. This theorem is the generalization of a similar result known for linear time-invariant and ideal switched capacitor networks. A major contribution of this paper is the second theorem, called the frequency reversal theorem, which gives an efficient way to compute the aliasing transfer functions of linear periodically time-varying circuits. The use of both of these theorems results in an efficient algorithm for noise analysis of linear periodically time-varying circuits in the frequency domain. The algorithm handles general PSL circuits, including switched capacitor and switched current networks with both white and 1/f noise sources. It has been implemented in a computer program. The output noise power of practical PSL circuits is analyzed and the results are compared with published measurement data.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".