نتایج جستجو برای: gaussian pdf
تعداد نتایج: 100218 فیلتر نتایج به سال:
Knowledge of the noise probability density function (PDF) is central in signal detection problems, not only for optimum receiver structures but also for processing procedures such as power normalization. Unfortunately, the statistical knowledge must be acquired since the classical assumption of a Gaussian noise PDF is often not valid in underwater acoustics. In this report, we study statistical...
We use the physics of ellipsoidal collapse to model the probability distribution function of the smoothed dark matter density field in real and redshift space. We provide a simple approximation to the exact collapse model which shows clearly how the evolution can be thought of as a modification of the spherical evolution model as well as of the Zeldovich Approximation (Zel’Dovich 1970). In esse...
MRI is one of the most powerful techniques to study the internal structure of the body. MRI image quality is affected by various noises. Noises in MRI are usually thermal and mainly due to the motion of charged particles in the coil. Noise in MRI images also cause a limitation in the study of visual images as well as computer analysis of the images. In this paper, first, it is proved that proba...
It is well known that the probability distribution function (PDF) of galaxy density contrast is approximately lognormal; whether the PDF of mass fluctuations derived from weak lensing convergence (κWL) is lognormal is less well established. We derive PDFs of the galaxy and projected matter density distributions via the Counts in Cells (CiC) method. We use maps of galaxies and weak lensing conve...
We address the problem of speaker clustering for robust unsupervised speaker diarization. We model each speakerhomogeneous segment as one single full multivariate Gaussian probability density function (pdf) and take into consideration the Riemannian property of Gaussian pdfs. By assuming that segments from different speakers lie on different (possibly intersected) sub-manifolds of the manifold ...
In a two node communication environment, the number of key bits (IK) per observation of the reciprocal channel can be computed using the mutual information between the forward and reverse estimated channels. The mutual information can not be computed in closed form, if the probability density function (pdf) of the channel is unknown. This work studies the computation of IK for an arbitrary chan...
Research in distributed video coding for low complexity encoding has shown that without knowledge of the correlation between source and side information (i.e. the behavior of the virtual dependency channel), the performance is substantially below that of well known state-of-the-art video coders. In this paper we investigate the modeling of the virtual channel for a pixel-based Wyner-Ziv coding ...
This paper proposes the use of Gaussian Mixture Models to estimate conditional probability density functions in an environmental risk mapping context. A conditional Gaussian Mixture Model has been compared to the geostatistical method of Sequential Gaussian Simulations and shows good performances in reconstructing local PDF. The data sets used for this comparison are parts of the digital elevat...
Solving the Fokker-Planck equation for high-dimensional complex turbulent dynamical systems is an important and practical issue. However, most traditional methods suffer from the curse of dimensionality and have difficulties in capturing the fat tailed highly intermittent probability density functions (PDFs) of complex systems in turbulence, neuroscience and excitable media. In this article, ef...
This paper presents convergence results for the Box Gaussian Mixture Filter (BGMF). BGMF is a Gaussian Mixture Filter (GMF) that is based on a bank of Extended Kalman Filters. The critical part of GMF is the approximation of probability density function (pdf) as pdf of Gaussian mixture such that its components have small enough covariance matrices. Because GMF approximates prior and posterior a...
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