Use of Discrete Orthonormal S-Transform to Simulate Earthquake Ground Motions
Bibliographic record
Abstract
ABSTRACT The S-transform and discrete orthonormal S-transform (DOST) produce time–frequency representations, which is in contrast to the wavelet transformations. Similar in the Fourier transform, the use of the S-transform and DOST provides frequency-dependent resolution with absolutely referenced phase information. Although the decomposed signal using DOST is expressed as a sum of orthonormal basis function, this is not the case if the S-transform is used. In the present study, a procedure to simulate nonstationary ground motions based on DOST is proposed based on a seed record or given a target amplitude of DOST coefficients. It is shown that the model has zero mean, and its variance equals the assigned target. Using five real records, each from a larger earthquake, the application of the DOST and S-transform to the records is carried out. Although the time–frequency resolution obtained from DOST is coarse as compared to that obtained using the S-transform, its use identifies clearly time–frequency characteristics. Samples of ground motions are simulated using the proposed method based on the amplitude of the DOST coefficients of a seed record or on the average amplitude of the DOST coefficients of a set of actual records. The comparison of the time–frequency resolution, Fourier spectrum, time-varying power distribution, and response spectrum of the simulated and seed records indicates that the proposed simulation model is a useful and practical tool to simulate nonstationary ground motions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".