Stability and steady state analysis of mode lock state of medium coupled microwave oscillators
Bibliographic record
Abstract
Abstract Coupled microwave oscillators could be potentially considered a good replacement for the feed network of frequency‐diverse arrays. However, previous studies showed that the stability region for a mutually weak‐coupled oscillator array in the Mode Lock State (MLS) is too small to be practical. Besides, by increasing the coupling strength or reducing the initial natural frequency of the oscillators, the current analytical methods lose their accuracy. The final steady‐state and dynamic of a non‐linear Van‐der‐Pol medium‐coupled oscillator array in the MLS is investigated. By using the Kuramoto Model results in analysing the biological cells, an alternative approach is suggested and investigated in the entrainment region for the mode‐locked microwave oscillator array. This approach is accurate even for medium‐coupled oscillator arrays, where the locking range to the beat frequency ratio is greater than 0.1. The stability of the oscillator in this region is investigated by imposing some perturbations in the form of phase noise on the initial signals. Also, the optimum initial condition to design large arrays is investigated using the analysis results. In the described initial conditions for small beat frequencies, the simulation results show that the stability region is much greater than the large beat frequency region. This capability initiates a new practical approach for implementing Frequency Diverse Arrays.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".