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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21 Mar 2004
TL;DR: This work derives bounds on the pairwise error probability (PEP) for each fading model and applies the transfer function technique in conjunction with derived PEP bounds to obtain bit error rate performance.
Abstract: We analyze the error rate performance of coded wireless optical links operating over atmospheric channels, where the turbulence-induced fading is modeled by the negative exponential distribution, K distribution and I-K distribution. First, we derive bounds on the pairwise error probability (PEP) for each fading model and then apply the transfer function technique in conjunction with derived PEP bounds to obtain bit error rate performance. Simulation results are also included to confirm the analytical results.
20 citations
TL;DR: In this article, a multivariate version of the central limit theorem is obtained that provides a convenient alternative to the one recently presented in [S. Umarov, C. Tsallis, S. Steinberg, cond-mat/0603593].
20 citations
TL;DR: In this article, the authors used the method of moments and L-moments (LMO) for determination of parameters of six probability distributions for estimation of maximum flood discharge (MFD) at a desired location on a river.
Abstract: Estimation of maximum flood discharge (MFD) at a desired location on a river is important for planning, design and management of hydraulic structures This can be achieved using deterministic models with extreme storm events or through frequency analysis by fitting of probability distributions to the recorded annual maximum discharge data In the latter approach, suitable probability distributions and associated parameter estimation methods are applied In the present study, method of moments and L-moments (LMO) are used for determination of parameters of six probability distributions Goodness-of-Fit tests such as Chi-square and Kolmogorov–Smirnov are applied for checking the adequacy of fitting of probability distributions to the recorded data Diagnostic test of D-index is used for the selection of a suitable distribution for estimation of MFD The study reveals that the Extreme Value Type-1 distribution (using LMO) is better suited amongst six distributions used in the estimation of MFD at Mal
20 citations
01 Jan 2009
TL;DR: In this paper, some size-biased probability distributions and their generalizations have been introduced, which provide a unifying approach for the problems where the observations fall in the non-experimental, non- replicated, and non-random categories.
Abstract: In this paper, some size-biased probability distributions and their generalizations have been introduced. These distributions provide a unifying approach for the problems where the observations fall in the non-experimental, non- replicated, and nonrandom categories. These distributions take into account the method of ascertainment, by adjusting the probabilities of actual occurrence of events to arrive at a specification of the probabilities of those events as observed and recorded. Failure to make such adjustments can lead to incorrect conclusions. This paper surveys some of the possible uses of size- biased distribution theory to some real life data.
20 citations
TL;DR: The order parameter of the K-distribution can be a promising new parameter to estimate the forest biomass from high-resolution polarimetric SAR data in a much wider range than the conventional RCS method.
Abstract: The purpose of this letter is to present the results on the study of searching effective parameters that describe the relation between high-resolution synthetic aperture radar (SAR) images and forest parameters The study is based on the non-Gaussian texture analysis of the polarimetric airborne Pi-SAR data over coniferous forests in Hokkaido, Japan The radar cross section (RCS) in terms of a forest biomass is first analyzed It is found that the L-band RCS increases steadily with the biomass and saturates at approximately 40 tons/ha These results are similar to the previous studies The probability density function of the image amplitude is then investigated, and among Rayleigh, log-normal, Weibull, and K-distributions, the K-distribution is found to fit best to the L-band data of all polarizations, although the Weibull distribution fits equally well Further, the correlation between the tree biomass and the order parameter of the K-distribution in the cross-polarization images is found to be very high, and the order parameter increases consistently with the biomass to approximately 100 tons/ha, which is well beyond the saturation limit of the L-band RCS Thus, the order parameter of the K-distribution can be a promising new parameter to estimate the forest biomass from high-resolution polarimetric SAR data in a much wider range than the conventional RCS method
20 citations