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Examples of amplitude normalized ST-RFT spectrograms P s (k, q) (a normalization with respect to its maximum value of each ST-RFT spectrogram S s (k, q))of 5 modulations computed from a sample of length N = 4000 with a Rectangular window of length H = 400 are shown in Fig. 2a-e.
Once the noise vector was estimated, a random sample of length 100 was taken and the tests were applied to this vector.
To construct the sampling distribution for a single parameter set and sample of length n, we ran 100 simulations of the model and obtained a sample of n contiguous time steps from each of the 100 runs.
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It is worth noting that for the sampling frequency of 44.1 kHz or higher, the samples of length 10 s in number keep almost unchanged.
To evaluate possible finite sample size distortions, we generate 10,000 samples of length 200 (equivalent to 50 years of quarterly data) of the following model begin{aligned} left.
The STFT was computed using Hann windows of 1024 samples of length, with a hop size of 512 samples (50% overlap).
To clarify the influence of the wire construction on AC loss, single and six filament untwisted samples of length ∼50 mm were examined.
To evaluate possible finite sample size distortions, we generate 10,000 samples of length 200 of the following model begin{aligned} left.
Next, we simulate and estimate 5000 samples of length 200 of four alternative DGPs analogous to the ones described in a.-d. of the previous section.
We show that smolder waves propagating in porous samples of length L do (do not) exhibit a transition to flaming if LF<L (LF>L).
Then, if we met a set of noise-only samples of length less than an SIFS, it means that the algorithm took the wrong decision and Φ u) will be forced to 1 for those samples.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com