Estimation of Wavelet Coherence of Seismic Ground Motions
Bibliographic record
Abstract
ABSTRACT The relation between the nonstationary seismic ground motions at two sites is often characterized using lagged coherence and phase spectrum. Their evaluation is most often carried out using ordinary Fourier analysis (i.e., without windowing) by assuming that they are time invariant. In the present study, the assessment of time-varying coherence is carried out based on the auto- and cross-wavelet power spectrum. The coherence is expressed in terms of lagged wavelet coherence and wavelet phase spectrum. For the analysis, the generalized Morse wavelets are employed, and the ground-motion records for several events from dense arrays located in Taiwan are used. It was shown that without adequate smoothing in scale and time, the obtained lagged wavelet coherence varies drastically in time and frequency (i.e., scale). A parametric analysis shows that the estimated coherence is sensitive to the degree of smoothing. The results of the lagged wavelet coherence and wavelet phase spectrum are time varying and frequency varying. This is in contrast with the time-invariant lagged coherence and phase spectrum assumed for the amplitude modulated evolutionary stochastic process. It is inferred from the results that the use of a time-varying coherence should be considered for seismic ground motions modeled as nonstationary processes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".