In the recent paper by Cetinkaya et al , admission control tests are derived by approximating the sum of two Gumbel distributed random variables by a Gumbel distributed random variable. In fact, the sum of two Gumbel distributed random variables does not follow a Gumbel distribution. Here, explicit expressions are derived for the probability density function (pdf) and the cumulative distribution function (cdf) of the exact distribution of the sum. The discrepancy between the exact and the approximate distributions is studied numerically.

It is pointed out that the two beta-type distributions introduced by Tardon et al. have been known before in the statistics literature.

Maximum and minimum of correlated Gaussian random variables arise naturally with respect to statistical static time analysis. It appears, however, that only approximations have been used in the literature to study the distribution of the max/min of correlated Gaussian random variables. In this paper, we would like to point out that the statistics literature has long established simple expressions for the exact distribution of the max/min. We provide some of the known expressions for the following: the probability density function, moment generating function, and the moments. We also provide two simple programs for computing the probability density functions of the max/min and an illustration of the results to statistical static time analysis.

Abstract The bit error probability (BEP) for many wireless communications networks can be expressed in the form R = Pr (X2 < X1) where X1 and X2 are independent random variables. Here, a comprehensive collection of formulas is derived for R by assuming the most commonly known models for X1 and X2. A discussion is provided of four possible applications to problems in wireless communications. Copyright © 2007 John Wiley & Sons, Ltd.

Simpler forms are derived for the properties of trivariate and quadrivariate Rayleigh distributions considered by Chen and Tellambura

Closed-form expressions are derived for the minimum duration outage and the probability of outage considered by Lai and Mandayam in the above paper.

A closed-form expression is derived for the moment generating function of the Weibull distribution when its shape parameter is a rational number.

For original paper, see Nikolaidis and Pitas (IEEE Trans. Image Process., vol.12, no.5, p.563-71, May 2003). Explicit expressions are derived for the Fisher information for the generalized Gaussian noise model considered by Nikolaidis and Pitas

Gierull provides a statistical analysis of multilook synthetic aperture radar interferograms. Various expressions for the probability density function, cumulative distribution function, and the moments of associated statistics are derived. It appears, however, that most of these expressions are based on some approximation. In this letter, the corresponding expressions are derived in their exact form, including some elementary representations for certain expressions given by Gierull. A numerical comparison of the exact and approximate expressions is provided

Explicit expressions are derived for the cumulants and the cumulant-generating function of the log-transformed radar cross section considered by Solbo and Eltoft. Some computational issues are also discussed

Explicit expressions are derived for the actual discrete cosine transform (DCT) coefficient distribution. Associated estimation procedures are also derived for ready use in practical applications

Since the turn of the century, several papers have appeared in reliability journals (including the IEEE Transactions on Reliability) which claim to have proposed new modifications of the traditional Weibull distribution. It is pointed out here that the proposed distributions are either not new, or arise from a representation suggested by Gurvich et al. . A modification is suggested that contains all of the proposed distributions as particular cases.