Search results for "probability density function"
showing 10 items of 183 documents
Group Metropolis Sampling
2017
Monte Carlo (MC) methods are widely used for Bayesian inference and optimization in statistics, signal processing and machine learning. Two well-known class of MC methods are the Importance Sampling (IS) techniques and the Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce the Group Importance Sampling (GIS) framework where different sets of weighted samples are properly summarized with one summary particle and one summary weight. GIS facilitates the design of novel efficient MC techniques. For instance, we present the Group Metropolis Sampling (GMS) algorithm which produces a Markov chain of sets of weighted samples. GMS in general outperforms other multiple try schemes…
Recycling Gibbs sampling
2017
Gibbs sampling is a well-known Markov chain Monte Carlo (MCMC) algorithm, extensively used in signal processing, machine learning and statistics. The key point for the successful application of the Gibbs sampler is the ability to draw samples from the full-conditional probability density functions efficiently. In the general case this is not possible, so in order to speed up the convergence of the chain, it is required to generate auxiliary samples. However, such intermediate information is finally disregarded. In this work, we show that these auxiliary samples can be recycled within the Gibbs estimators, improving their efficiency with no extra cost. Theoretical and exhaustive numerical co…
Path Integral approach via Laplace’s method of integration for nonstationary response of nonlinear systems
2019
In this paper the nonstationary response of a class of nonlinear systems subject to broad-band stochastic excitations is examined. A version of the Path Integral (PI) approach is developed for determining the evolution of the response probability density function (PDF). Specifically, the PI approach, utilized for evaluating the response PDF in short time steps based on the Chapman–Kolmogorov equation, is here employed in conjunction with the Laplace’s method of integration. In this manner, an approximate analytical solution of the integral involved in this equation is obtained, thus circumventing the repetitive integrations generally required in the conventional numerical implementation of …
Stress Detection from Speech Using Spectral Slope Measurements
2018
Automatic detection of emotional stress is an active research domain, which has recently drawn increasing attention, mainly in the fields of computer science, linguistics, and medicine. In this study, stress is automatically detected by employing speech-derived features. Related studies utilize features such as overall intensity, MFCCs, Teager Energy Operator, and pitch. The present study proposes a novel set of features based on the spectral tilt of the glottal source and of the speech signal itself. The proposed features rely on the Probability Density Function of the estimated spectral slopes, and consist of the three most probable slopes from the glottal source, as well as the correspon…
The Influence of LOS Components on the Statistical Properties of the Capacity of Amplify-and-Forward Channels
2009
Also available from publisher: http://dx.doi.org/10.4236/wsn.2009.11002 Amplify-and-forward channels in cooperative networks provide a promising improvement in the network coverage and system throughput. Under line-of-sight (LOS) propagation conditions in such cooperative networks, the overall fading channel can be modeled by a double Rice process. In this article, we have stud-ied the statistical properties of the capacity of double Rice fading channels. We have derived the analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level- crossing rate (LCR), and average duration of fades (ADF) of the channel capacity. The obtained results ar…
Modeling and statistical characterization of wideband indoor radio propagation channels
2010
In this paper, we focus on the modeling of wideband single-input single-output (SISO) mobile fading channels for indoor propagation environments. The derived indoor reference channel model is based on a geometrical scattering model, which consists of an infinite number of scatterers uniformly distributed over the two-dimensional (2D) horizontal plane of a rectangular room. We derive analytical expressions for the probability density function (PDF) of the angle of arrival (AOA), the power delay profile (PDP), and the frequency correlation function (FCF). An efficient sum-of-cisoids (SOC) channel simulator will be derived from the proposed non-realizable reference model. It is shown that the …
Nonequilibrium effective temperature of superfluid vortex tangle
2006
An effective nonequilibrium temperature in counterflow superfluid turbulence is proposed, as a parameter characterizing a canonical probability distribution function of vortex orientation, and relating the diffusion coefficient of vortex lines to the vortex friction through an Einstein relation.
Uncertainty quantification analysis of the biological Gompertz model subject to random fluctuations in all its parameters
2020
[EN] In spite of its simple formulation via a nonlinear differential equation, the Gompertz model has been widely applied to describe the dynamics of biological and biophysical parts of complex systems (growth of living organisms, number of bacteria, volume of infected cells, etc.). Its parameters or coefficients and the initial condition represent biological quantities (usually, rates and number of individual/particles, respectively) whose nature is random rather than deterministic. In this paper, we present a complete uncertainty quantification analysis of the randomized Gomperz model via the computation of an explicit expression to the first probability density function of its solution s…
Morphostatistical characterization of the spatial galaxy distribution through Gibbs point processes
2021
This paper proposes a morpho-statistical characterisation of the galaxy distribution through spatial statistical modelling based on inhomogeneous Gibbs point processes. The galaxy distribution is supposed to exhibit two components. The first one is related to the major geometrical features exhibited by the observed galaxy field, here, its corresponding filamentary pattern. The second one is related to the interactions exhibited by the galaxies. Gibbs point processes are statistical models able to integrate these two aspects in a probability density, controlled by some parameters. Several such models are fitted to real observational data via the ABC Shadow algorithm. This algorithm provides …
Non-Markovian master equation for the XX central spin model
2008
The non-Markovian correlated projection operator technique is applied to the model of a central spin coupled to a spin bath through non uniform XX Heisenberg coupling. The second order results of the Nakajima-Zwanzig and of the time-convolutionless methods are compared with the exact solution considering a fully polarized initial bath state.