Topic
K-distribution
About: K-distribution is a research topic. Over the lifetime, 1281 publications have been published within this topic receiving 51774 citations.
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TL;DR: In this article, a large class of bivariate distributions (beta, Pareto, gamma, negative binomial, Poisson, binomial) and their limiting distributions are derived.
16 citations
TL;DR: In this article, the influence of the relative scattering strength of seafloor patches on scattered envelope statistics was explored through both a modified form of a recently developed model [Abraham and Lyons, IEEE J. Ocean. Eng., vol. 27, pp. 800-813, 2002] and analysis of experimental data collected off Elba Island, Italy, in May 2003, by the NATO Undersea Research Centre, La Spezia, Italy.
Abstract: The scattering properties of the individual components of seafloors consisting of discrete patches of different materials may have a complicated relationship in terms of their angular response and/or frequency dependence. Consequently, this relationship directly influences the angular and frequency response of scattered envelope probability density functions (pdfs). In this paper, the influence of the relative scattering strength of seafloor patches on scattered envelope statistics will be explored through both a modified form of a recently developed model [Abraham and Lyons, IEEE J. Ocean. Eng., vol. 27, pp. 800-813, 2002] and analysis of experimental data collected off Elba Island, Italy, in May 2003, by the NATO Undersea Research Centre, La Spezia, Italy. Qualitative comparisons of the K-distribution shape parameter (alpha) between that predicted by the model and that measured from data display promising similarities such as the inverse relationship between alpha and bandwidth, the relative difference in values of alpha for the various seafloor types studied, and the dependence on grazing angle. The favorable model/data comparisons show that it is possible to link the scattered envelope distribution to measurable geoacoustic properties, providing the foundation necessary for solving several important problems related to the detection of targets in non-Rayleigh clutter including performance prediction for different systems based on seafloor properties, extrapolation of performance to other system/bandwidths, and optimization of system parameters such as bandwidth to local environment.
15 citations
15 citations
18 Sep 2006
TL;DR: An algorithm for learning Kikuchi approximations from data based on the expectation-maximization (EM) paradigm is presented and the proposal is tested in the approximation of probability distributions that arise in evolutionary computation.
Abstract: Mixtures of distributions concern modeling a probability distribution by a weighted sum of other distributions. Kikuchi approximations of probability distributions follow an approach to approximate the free energy of statistical systems. In this paper, we introduce the mixture of Kikuchi approximations as a probability model. We present an algorithm for learning Kikuchi approximations from data based on the expectation-maximization (EM) paradigm. The proposal is tested in the approximation of probability distributions that arise in evolutionary computation.
15 citations
TL;DR: The stationary birth-only, or Yule-Furry, process for rooted binary trees has been analysed with a view to developing explicit expressions for two fundamental statistical distributions: the probability that a randomly selected leaf is preceded by N nodes, or "ancestors", and the likelihood that two randomly selected leaves are separated by N node.
15 citations