In the paper, parameters of 115 types existing wind turbines (WT) were analyzed and their power curves modeled by using Weibull cumulative distribution function (CDF). On basis these data, regression equations obtained for CDF WT due to main sizes: nameplate capacity generator P rotor D. Based on analysis sizes, model average used (AUP) in specific conditions has been built. The area existence ...

In this article, we have proposed a new distribution having three parameters using half Cauchy family of called Half-Cauchy Exponential extension Distribution. The statistical properties as well different characteristics like the hazard rate function (HRF), probability density (PDF), cumulative (CDF), quantile function, skewness, and kurtosis are discussed. estimated by least-square estimation ...

We present a new wireless scheduling algorithm based on the cumulative distribution function (cdf) of user transmission rates and also present a simple modification of it to limit the maximum starving time. This cdf-based scheduling (CS) algorithm selects the user for transmission based on the cdf of user rates in such a way that the user whose rate is high enough but least probable to become h...

This paper focuses on providing an analytical framework for the quantification and evaluation of pointing error a general case at high-frequency millimeter wave (mmWave) terahertz (THz) communication links. For this aim, we first derive probability density function (PDF) cumulative distribution functions (CDF) between unstable transmitter (Tx) receiver (Rx), that have different antenna patterns...

In this paper, we derive recurrence relations for cumulative distribution functions (cdf’s) of bivariate t and extended skew-t distributions. These recurrence relations are over ν (the degrees of freedom), and starting from the known results for ν = 1 and ν = 2, they will allow for the recursive evaluation of the distribution function for any other positive integral value of ν. Then, we conside...

1 Sum of Bernoulli Distributions Here are some basic statistical concepts needed to perform statistical analysis on binary images. Given a sample space S, a random variable X is a rule that assigns a number to each element of S. X is a function that maps element s ∈ S to a real number, i.e. X : S → R. Bernoulli random variable X takes values only 0 or 1. The probability distribution P of a rand...

We show that a simple, general, and easily reproducible method for generating non-uniform sampling (NUS) schedules preserves the benefits of random sampling, including inherently reduced sampling artifacts, while removing the pitfalls associated with choosing an arbitrary seed. Sampling schedules are generated from a discrete cumulative distribution function (CDF) that closely fits the continuo...

• For a discrete RV the mass function is pX(x) = P (X = x). The continuous analog is the probability density function (pdf) that may be interpreted as fX(x) ≈ P (x < X < x+ ∆)/∆ as 0 < ∆→ 0. • The cumulative distribution function (cdf) FX(x) = P (X ≤ x) is the probability that X is less than or equal to a specific value. In the continuous case we have fX(x) = dFX(x)/dx and FX(x) = ∫ x −∞ fX(r)d...

For the purpose of attaining a high degree freedom (DOF) for direction arrival (DOA) estimations in radar technology, coprime sensor arrays (CSAs) are evaluated this paper. In addition, global and local minima extremely non-linear functions investigated, aiming to improve DOF. The optimization features cuckoo search (CS) algorithm utilized DOA estimation far-field sources low signal-to-noise ra...

In piecewise-deterministic Markov processes (PDMPs) the state of a finite-dimensional system evolves continuously, but evolutive equation may change randomly as result discrete switches. A running cost is integrated along corresponding trajectory up to termination produce cumulative process. We address three natural questions related uncertainty in PDMP models: (1) how compute distribution func...