نتایج جستجو برای: probability density function pdf
تعداد نتایج: 1751231 فیلتر نتایج به سال:
Various existing criteria to characterize the statistical independence are applied in blind source separation and independent component analysis. However, almost all of them are based on parametric models. The distribution model mismatch between the output PDF (Probability Density Functions) and the chosen underlying distribution model is a serious problem in blind signal processing. Non-parame...
The adaptive rejection sampling (ARS) algorithm is a universal random generator for drawing samples efficiently from a univariate log-concave target probability density function (pdf). ARS generates independent samples from the target via rejection sampling with high acceptance rates. Indeed, ARS yields a sequence of proposal functions that converge toward the target pdf, so that the probabilit...
This paper studies the performance of switch and stay combining (SSC) diversity receivers operating over correlated Ricean fading satellite channels. Using an infinite series representation for the bivariate Ricean probability density function (PDF), the PDF of the SSC output signal-to-noise ratio (SNR) is derived. Capitalizing on this PDF, analytical expressions for the corresponding cumulativ...
Spectral kurtosis (SK) is a statistical approach for detecting and removing radio-frequency interference (RFI) in radio astronomy data. In this article, the statistical properties of the SK estimator are investigated and all moments of its probability density function are analytically determined. These moments provide a means to determine the tail probabilities of the estimator that are essenti...
Spectral Kurtosis (SK) is a statistical approach for detecting and removing radio frequency interference (RFI) in radio astronomy data. In this study, the statistical properties of the SK estimator are investigated and all moments of its probability density function are analytically determined. These moments provide a means to determine the tail probabilities of the estimator that are essential...
Expressions of ASER for different M-ary modulations and outage probability of dual pre-detection equal gain combining (EGC) receiver have been derived over correlated Nakagami-m fading channels with arbitrary and non-identical fading parameters. A classical probability density function (PDF) based approach has been used to obtain expressions of different performance measures. The mathematical a...
In this paper we evaluated the performance of orthogonal space-time block codes with transmit antenna selection (TAS/OSTBCs) for frequency-flat correlated Rayleigh fading channels. By effective use of the probability density function (pdf), the bit error probability (BEP) for binary phase shift keying (BPSK) and M-ary Quadrature amplitude modulation (M-QAM) is derived first. Further we evaluate...
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...
With the assumption that the bed shear stress fluctuates in a lognormal fashion, the probability density function (pdf) of the standardised bed shear stress is derived as a function of the relative shear stress intensity. The pdf is more skewed with larger relative intensities, but approaches a Gaussian function when the relative intensity is small. The computed pdf agrees well with the reporte...
The probability density function (PDF), and its corresponding cumulative density function (CDF), provide direct statistical insight into the characterization of a random process or field. Typically displayed as a histogram, one can infer probabilities of the occurrence of particular events. When examining a field over some two-dimensional domain in which at each point a PDF of the function valu...
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