Wide Band Time-Correlated Model for Wireless Communications under\n Impulsive Noise within Power Substation
Bibliographic record
Abstract
The installation of wireless technologies in power substations requires\ncharacterizing the impulsive noise produced by the high-voltage equipment.\nSubstation impulsive noise might interfere with classic wireless communications\nand none of the existing models can reliably represent this noise in wide band.\nPrevious studies have shown that impulsive noise is characterized by series of\ndamped oscillations with the amplitude, the duration and the occurrence times\nof the impulses that are random. All these characteristics make this noise\ntime-correlated and the partitioned Markov chain remains an efficient model\nthat can ensure the correlation between the samples. In this study, we propose\nto design a partitioned Markov chain to generate an impulsive noise that is\nsimilar to the noise measured in existing substations, in time and frequency\ndomains. We configure our Markov chain to produce the impulses with the damped\noscillation effect, then, we determine the probability transition matrix and\nthe distribution of each state of the Markov chain. Finally, we generate noise\nsamples and we study the distribution of the impulsive noise characteristics.\nOur Markov chain model can replicate the correlation between the measured noise\nsamples; also the distributions of the noise characteristics are similar in the\nsimulations and the measurements.\n
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".