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Furthermore, it is difficult to represent the original HR frame x (i) by using a simple fixed distribution, and we have to model it by using a distribution whose shape can adaptively be determined for each area based on its parameters β (i).
By using a distribution function of f, the function f^(x):=sup biggl{ 0le tlesup_{J} f: D_{f,J}(t ge2bigglvert x-frac{a+b}{2}biggrvert biggr},quad x in J is called a symmetrical decreasing rearrangement (SDR) of f, because it is increasing in ([a,frac{a+b}{2}]) and decreasing on ([ frac{a+b}{2},b]).
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To prevent a continuous signal pattern, we introduced variation by using a Poisson distribution consistent with the cumulative distribution.
In each iteration, the (complex) reference distribution is approximated using a simple probability distribution; we illustrate the method by using a multinomial distribution, whose parameters are estimated by maximum likelihood estimation in each iteration, using the conformations generated in the previous iteration.
To predict the probability distribution of the peak sidelobe levels, distributions of levels were modelled by using a Weibull distribution at each peak in the sidelobe region of the mean squared magnitude of the aperture smoothing function.
It focuses on generating as complete a picture of the potential risk as possible by using a probability distribution that allows us to clearly observe the characteristics of any "fat tails" associated with the distribution.
The relative bias using a Student- t distribution was never above 0.2%, but smaller than the one obtained by using a normal distribution (Table 3).
Several new models relax this constraint by estimating dN and dS separately from discrete distributions of n categories (n > =3) [ 30], or by using a gamma distribution [ 31].
By using a pTAS distribution one always has greater flexibility to account for semi-heavy (or not so heavy) tailed distributions compared to a lognormal or a gamma distribution.
Preliminary measurements, performed by using a pressure distribution analysis, were carried out to qualitatively locate the LSB presence.
The locations and severities of damages are characterized by using a damage distribution function, and a damaged small material volume is represented by the effective orthotropic elastic stiffnesses, which are derived in terms of damage orientation and size.
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