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Based on these parameters the power lost in the pump can be calculated from Eq. 11: Delta P_{text{pump}} = 73, left( {1 - 66/100} right) = 24.8;{text{HP}} = 18.5; {text{kW}}.
Based on these parameters the power lost in the pump can be calculated as (Eq. 11): Delta P_{text{pump}} = 29, left( {1 - 65/100} right) = 10.2;{text{HP}} = 7.6; {text{kW}}.
Depending on the values of these parameters, the power spectral density of the analysed load can be of wide-band character (as for the Fung's spectrum), more or less narrow-band character (as for the spectrum of a Gauss curve-type), or in a particular case, of δ-Dirac spectrum type.
Changes in muscle activity during (static and dynamic) position tasks have been assessed using two of the three traditional sEMG parameters, the power spectrum and the global sEMG amplitude.
With 10 measurement times and the same value for all other parameters, the power of the LPCM method decreased to 52% while that of the SM method was around 99%.
Both growth charts contain the Lambda-Mu-Sigma (LMS) parameters (the power in the Box-Cox transformation (L), the median (M), and the generalized coefficient of variation (S)) needed to generate exact percentiles and z-scores by age and gender [ 32].
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A simple average rate optimization algorithm: In contrast to transmission power parameters, the power-limited average rate optimization problem of quantized CSI-based systems, e.g., (13), is not a convex optimization problem in terms of quantization parameters ĝ i, g ̃ i ∀ i [34 38].
The first method uses the SVR technique to identify nonlinear structural parameters, whereby the power parameter controlling the shape of the Bouc Wen model is known.
Moreover, the effects of the step-size parameter, the power spectra of the input signals, and multiple secondary paths can be evaluated individually at each frequency bin.
It also allows modelling the crack growth variation in all specimens by varying only one parameter, the power law exponent for the plane strain condition.
(lambda _1), (lambda _2), (lambda _3) are parameters controlling the power of regularization to each parameters in the neural network.
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