K-distribution

About: K-distribution is a research topic. Over the lifetime, 1281 publications have been published within this topic receiving 51774 citations.

On Sample Size in Using Central Limit Theorem for Gamma Distribution

Abstract: A general criterion in using the central limit theorem is based on the sample size n > 30, no matter what the population is. Such only one generalized criterion may not be suitable for various shapes of probability distributions. This study is to check gamma distribution, one of asymmetric continuous distributions, how fit that criterion by computer simulation techniques, and finds out the least required sample sizes that satisfy the central limit theorem under different parameters of the gamma distribution.

Estimating state probability distributions from noisy and corrupted data

Abstract: The method of recursive state density estimation (RSDE) is developed for determining the probability distribution of the states of a system from measurements that contain both random noise and gross errors. The technique is based on the expectation maximization algorithm and is iterative in nature. Similar to EM, at each iteration the likelihood of the distribution estimated by the RSDE algorithm is guaranteed to increase, thus arriving at the most likely distribution of the true states, given the measurement data set and the algorithm initial conditions. Convergence of the algorithm to the correct solution, for a simple case where an analytical answer can be derived for comparison, is shown. Two chemical process examples that have more complex distributions are also shown. Once the probability distribution of the states has been determined, many monitoring and statistical process and quality control functions can be performed using the more accurate distributions of the process states, avoiding corruption of the distribution due to faulty measurements.

Compounding: an R package for computing continuous distributions obtained by compounding a continuous and a discrete distribution

Abstract: In this manuscript we introduce R package Compounding for dealing with continuous distributions obtained by compounding continuous distributions with discrete distributions. We demonstrate its use by computing values of cumulative distribution function, probability density function, quantile function and hazard rate function, generating random samples from a population with compounding distribution, and computing mean, variance, skewness and kurtosis of a random variable with a compounding distribution. We consider 24 discrete distributions which can be compounded with any continuous distribution implemented in R.

The analysis of sea clutter statistics characteristics based on the observed sea clutter of Ku-band Radar

Abstract: The model of GTI, TSC, NRL distribution the most fundament characteristic of sea clutter, as used in radar performance evaluation. The model of Rayleigh, LogNormal, Weibull and K distribution radar clutter are analyzed and modeled and some kinds of radar clutter, such as ground, weather, chaff and sea clutter are modeled and simulated. The analysis focuses on amplitude characteristic of sea clutter. The analysis would contribute to designing and implementation of radar filter and increasing the ability of suppressing sea clutter and ensuring the detection ability of radar itself.