Table 1.

The distribution test for SFC, LNN and LDMM.

Distribution	Probability distribution function $f\left(x\right)$
Frechet distribution	$f\left(x,;,\alpha ,,,\beta \right)=\frac{\beta }{x}{\left(\frac{\alpha }{x}\right)}^{\beta }{e}^{-{\left(\frac{\alpha }{x}\right)}^{\beta }}$$x>0,$ $\alpha ,\beta >0,$
	where $\alpha ,$ $\beta$ are shape parameters.
Additive Gumbel Type II Distribution	$f\left(x,;,{\eta }_i,,,{\delta }_i\right)={\sum }_{i=1}^2{\eta }_i{\delta }_i{x}^{-{\eta }_i-1}{e}^{-{\sum }_{i=1}^2{\delta }_i{x}^{-{\eta }_i}}$ $x,$ $\left({\delta }_i,,,{\eta }_i\right)>0$
	Where the shape parameters are ${\delta }_i,$ ${\eta }_i$, $i=1,2.$
Gumbel Type II Distribution	$f\left(x,;,\eta ,,,\delta \right)=\eta \delta x^{-\eta -1}{e}^{-\delta x^{-\eta }}$ $\left(x,,,\delta ,,,\eta \right)>0,$
	Where the shape parameters are $\delta ,$ $\eta$.
Weibull Distribution	$f\left(x,;,\lambda ,,,\beta \right)=\frac{\beta }{\lambda }{\left(\frac{x}{\lambda }\right)}^{\beta -1}{e}^{-{\left(\frac{x}{\lambda }\right)}^{\beta }}$$x>0,$ $\lambda ,\beta >0,$
	where $\beta >0$ is the shape parameter and $\lambda >0$
	is the scale parameter of the distribution.
Modified Frechet distribution	$f\left(x,;,\alpha ,,,\beta ,,,\lambda \right)=\frac{1}{x}\left(\beta ,+,\lambda ,x\right){\left(\frac{\alpha }{x}\right)}^{\beta }exp\left[-,\lambda ,x,-,{\left(\frac{\alpha }{x}\right)}^{\beta }\right]$
	$x>0,$ $\alpha ,\beta >0,$ $\lambda \ge 0,$
	where $\alpha ,$ $\beta ,$ $\lambda$ are shape parameters.
Rayleigh Distribution	$f\left(x,;,\sigma \right)=\frac{x}{{\sigma }^2}exp\left[-,\frac{x^2}{2{\sigma }^2}\right]$
	where $\sigma$ is the scale parameter of the distribution.