This paper is concerned with the determination of tight lower and upper bounds on the expectation of a convex function of a random variable. The classic bounds are those of Jensen and ...

In this research note section 2 is devoted for characterization based on identity of distribution and equality of expectation function randomly variable for a negative exponential distribution with ...

In this paper, we study the distribution of the log-modulus of a Gaussian complex random variable. In the circular case, it is a Log-Rayleigh (LR) variable, whose probability distribution function ...

In this research note section 2 is devoted for characterization based on identity of distribution and equality of expectation function randomly variable for a negative exponential distribution with ...

Probability density function is a statistical expression defining the likelihood of a series of outcomes for a continuous variable, such as a stock or ETF return.

Notice that the sum of all probabilities in this table is 1. Since f (x,y) is a probability distribution, it must sum to 1. Adding probabilities across the rows you get the probability distribution of ...

A random variable is one whose value is unknown or a function that assigns values to each of an experiment’s outcomes. A random variable can be discrete or continuous.

This project about distribution of function of random variable. We used Geometric, Binomial, Poisson, Uniform distribution & their ploting using python. This project is Developed by Group C. Gr ...

One novel neuron with variable nonlinear transfer function is firstly proposed, It could also be called as subsection transfer function neuron. With different transfer function components, by virtue ...