نتایج جستجو برای: cumulative distribution function cdf
تعداد نتایج: 1801024 فیلتر نتایج به سال:
The distributions of random variables are of interest in many areas of science. In this paper, the probability density function PDF and cumulative distribution function CDF of ratio of products of two random variables and random variable are derived. Random variables are described with Rayleigh, Nakagami-m, Weibull, and α-μ distributions. An application of obtained results in performance analys...
This letter focuses on providing an analytical framework for the quantification and evaluation of pointing error at high-frequency millimeter wave (mmWave) terahertz (THz) communication links. For this aim, we first characterize channel a point-to-point link between unstable transmitter (Tx) receiver (Rx) then, derive probability density function (PDF) cumulative distribution functions (CDF) in...
An approach to the performance analyses of signal-to-interference (SIR) based selection combining (SC) operating over the correlated Rayleigh fading channels experiencing an arbitrary number of correlated multiple, co-channel interferers is presented. General analysis of multibranch SC where each correlated branch experiences an arbitrary number of multiple correlated co-channel interferers. In...
In this paper, relay based mobile to mobile (M2M) system employing amplify and forward (AF) protocol has been considered and its end to end performance over N-α-μ fading channels has been explored. The closed form expressions for probability density function (PDF), cumulative distribution function (CDF) of cascaded α-μ fading channels and lower bound on average symbol error probability (ASEP) h...
Intrinsically disordered proteins (IDPs) are associated with a wide range of functions. We suggest that sequence-based subtypes, which we call flavors, may provide the basis for different biological functions. The problem is to find a method that separates IDPs into different flavor / function groups. Here we discuss one approach, the (Charge-Hydropathy) versus (Cumulative Distribution Function...
This paper presents an illustration of how knowledge from the field special functions, orthogonal polynomials and numerical series can be applied to solve a very important problem in modern wireless communications. We present formulas for probability density function (PDF) cumulative distribution (CDF) composite signal envelope over mm-Wave channel. The PDF CDF are expressed convergent infinity...
Change-point hazard models have several practical applications, including modeling processes such as cancer mortality rates and disease progression. While the inverse cumulative distribution function (CDF) method is commonly used for simulating data, we demonstrate shortcomings of this approach when data from change-point distributions with more than a scale parameter. We propose an alternative...
This paper introduces the Method of Microwave Rainfall Normalization (MMN) for Global Satellite Mapping Precipitation (GSMaP) algorithm in its latest version (V05, 8), released December 2021. The method aims to mitigate discrepancy GSMaP rainfall estimates among passive microwave (PMW) imagers/sounders (MWIs/MWSs) due differences sensor specifications and retrieval algorithms. basic idea MMN mo...
The goal of this work is to employ a semi-analytical framework investigate key features associated with the transport behavior an inert solute in non-Gaussian random fields. We focus our analysis on dynamics plume through porous medium characterized by spatially heterogeneous log-conductivity fields, Y. rest stochastic Lagrangian provide formulations evaluate statistical moments and cumulative ...
As a promising technology, free-space optical (FSO) communication plays an important role in the next generation of wireless communication. A dual-hop FSO system with decode-and-forward (DF) protocol is proposed this paper, considering influences atmospheric turbulence (AT), absorption and pointing error impairments, which Málaga distribution model used to characterize fading caused by AT each ...
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