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For each of the treatments, the mean of the transcription signals was computed.
The average amplitude of 250 simulated and 20 measured PA signals was computed along with the standard deviation for each sample.
For both the acceleration and acoustic stimuli, the root-mean-squared (RMS) amplitude of the EMG signals was computed using a moving 20 ms window.
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While this is in general agreement with the notion of a saliency-based processing architecture, in which saliency signals are computed at different hierarchical levels, it remains an open issue whether these computations are integrated by an overall-saliency map, thereby modulating visual selection times.
The optimal signals are computed recursively using a predictive filter.
Numerical signals were computed using the Coulomb software package.
Time-frequency representations of the corresponding signals were computed by means of continuous wavelet transforms.
Features such as amplitude, phase and power spectrum of sound signals are computed via a 1024-point FFT.
Root-mean-squared (RMS) values of EMG signals were computed to compare the influence of experimental conditions on muscle strain.
Four chaotic invariants, which include the largest Lyapunov exponent, metric entropy, correlation dimension and mutual information, of all pressure signals are computed.
The wavelet coefficients and Lyapunov exponents of the ECG signals were computed and statistical features were calculated to depict their distribution.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com