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Showing papers on "K-distribution published in 1972"



Journal ArticleDOI
G.D. Finn1
TL;DR: In this article, a linear integral equation is formulated for the probability that a photon in a spectral line formed at a specified depth in a scattering atmosphere eventually escapes at a particular frequency in the spectral line.
Abstract: A linear integral equation is formulated for the probability that a photon in a spectral line formed at a specified depth in a scattering atmosphere eventually escapes at a particular frequency in the spectral line. Numerical solutions are obtained for an isothermal atmosphere and their physical meaning discussed under a variety of conditions.

8 citations


Journal ArticleDOI
Y. H. Wang1
01 Mar 1972

6 citations


01 Jan 1972
TL;DR: This paper summarizes recent work on the theory of epsilon entropy for probability distributions on complete separable metric spaces in order to have a framework for discussing the quality of data storage and transmission systems.
Abstract: This paper summarizes recent work on the theory of epsilon entropy for probability distributions on complete separable metric spaces. The theory was conceived [3] in order to have a framework for discussing the quality of data storage and transmission systems. The concept of data source was defined in [4] as a probabilistic metric space: a complete separable metric space together with a probability distribution under which open sets are measurable, so that the Borel sets are measurable. An a partition of such a space is a partition by measurable a sets, which, depending on context, can be sets of diameter at most e or sets of radius at most ie, that is, sets contained in spheres of radius 2e. The entropy H(U) of a partition U is the Shannon entropy of the probability of the distribution consisting of the measures of the sets of the partition. The (one shot) epsilon entropy of X with distribution A, He;,,(X), is defined by (1.1) He;p(X) = inf {H(U); U an c partition} U

4 citations


Journal ArticleDOI
TL;DR: In this article, approximate approximations to the distributions of order statistics based on x2t are obtained, which are easy to compute and provide reasonably accurate values for the percentage points and probability integrals of the distributions.
Abstract: SUMMARY Approximations to the distributions of order statistics based on x2t are obtained. These are easy to compute and provide reasonably accurate values for the percentage points and probability integrals of the distributions.

2 citations


01 Jun 1972
TL;DR: In this paper, the generalized incomplete modified Bessel distribution (GIBD) is developed and applications to various problems in system reliability are given, and properties of GIBD are investigated.
Abstract: : Properties of the generalized incomplete modified Bessel distributions are developed and applications to various problems in systems reliability are given (Author)

1 citations



Journal ArticleDOI
01 Dec 1972-Metrika
TL;DR: In this article, the entropy and inaccuracy of similarly and oppositely ordered discrete probability distributions have been discussed in detail and it is shown that these inaccuracies are monotonically increasing function of \ for oppositely-ordered distributions and decreasing function of β for similarly ordered distributions.
Abstract: This note deals with the entropy and inaccuracy of similarly and oppositely ordered discrete probability distributions. The concept of inaccuracy range has also been introduced. In particular, the inacuracy of β-Power distributions with respect to another distribution has been discussed in detail. It is shown that these inaccuracies are monotonically increasing function of \ for oppositely ordered distributions and decreasing function of β for similarly ordered distributions.

Journal ArticleDOI
01 Apr 1972
TL;DR: It is shown that for counts scattered about a true signal value in accord with the Poisson probability distribution, the optimum linear signal estimate is identical to the optimum nonlinear estimate if the signal has a gamma probability density.
Abstract: It is shown that for counts scattered about a true signal value in accord with the Poisson probability distribution, the optimum linear signal estimate is identical to the optimum nonlinear estimate if the signal has a gamma probability density.