This paper considers the partial decode-and-forward (PDF) strategy for the Gaussian multiple-input multiple-output (MIMO) relay channel. Unlike for the decode-and-forward (DF) strategy or pointto-point (P2P) transmission, for which Gaussian channel inputs are known to be optimal, the input distribution that maximizes the achievable PDF rate for the Gaussian MIMO relay channel has remained unkno...

For chance-constrained programming (CCP) with non-Gaussian uncertainty, the optimization is generally intractable owing to the complicated probability density function (PDF). Using a simple fitted distribution with Kullback-Leibler (KL) divergence to represent the PDF mismatch is a systematic way to tackle CCP with non-Gaussian uncertainty. However, the essential difficulty of this methodology ...

The problem of determining the distances and their uncertainties from the measurements of parallaxes has no straight forward solution. In contrast to Bayesian-like approaches, a direct approach is possible assuming that the probability density function (pdf) in relative distance is cut for negative distances. This gives an asymmetrical pdf which is difficult to use and overestimates variances. ...

In the context of digital signal processing addressed to underwater acoustic communications, this work focuses attention on the optimization of detection of weak signals in presence of additive independent stationary non-Gaussian noise. In order to detect signals in the case of low SNR values, the selected binary statistical testing approach consists in a Locally Optimum Detector (LOD), designe...

The probability density function (PDF) of the surface electromyogram (EMG) signals has been modelled with Gaussian and Laplacian distribution functions. However, a general consensus upon the PDF of the EMG signals is yet to be reached, because not only are there several biological factors that can influence this distribution function, but also different analysis techniques can lead to contradic...

We present an analysis for evaluating the probability density function (pdf) of the noise at the output of the frequency demodulator. It is shown that the noise is non-Gaussian and that for low to medium signal-to-noise power ratios, its pdf differs very significantly from the Gaussian pdf commonly assumed in simplified analysis. These results are very important for analyzing the performance of...

When a probability density function (pdf) is to be formed on the basis of incomplete information, the “maximum missing information” (mmi) pdf (Jaynes. Phys. Reo. 106, 62M30, 1957) is theoretically preferable. We compare the performance of Lagrangian stochastic (LS) models of vertical dispersion in the convective boundary layer. satisfying Thomson’s (J. Fluid Mech. 180,529-556, 1987) well-mixed ...

The gravitational evolution of the cosmic one-point probability distribution function (PDF) has been estimated using an analytic approximation that combines gravitational perturbation theory with the Edgeworth expansion around a Gaussian PDF. Despite the remarkable success of the Edgeworth expansion in modeling the weakly non-linear growth of fluctuations around the peak of the cosmic PDF, it f...

This paper presents a new approach to the real time single and multiple target detection and tracking problems with measurement input data. The new approach addresses the measurement uncertainty-of-origin issue by capturing all measurement input data information in the Bayesian conditional probability density function (PDF), used in the recursive propagation of the posterior target detection an...

Functional magnetic resonance (fMRI) studies intend to answer neuroscience questions by statistically analyzing a set of acquired images. Thereby, the aim is to determine those regions in the brain image in which the signal changes upon stimulus presentation. Although MR data are intrinsically complex valued, most tests are commonly applied to magnitude MR images, because these images have the ...