A full 3D numerical simulation of the two-phase flow made up (bio)diesel and particles, has been carried out to reproduce deposition pattern particles in a BOSCH automotive filter. From probability density function (PDF), simple Eulerian-Eulerian model is proposed for diesel particles. The formulation allows detailed description relationship between velocity size Brinkman-Darcy approximation co...

In literature, Extended Object Tracking (EOT) algorithms developed for autonomous driving predominantly provide obstacles state estimation in cartesian coordinates the Vehicle Reference Frame. However, many scenarios, representation road-aligned curvilinear is preferred when implementing subsystems like cruise control, lane-keeping assist, platooning, etc. This paper proposes a Gaussian Mixture...

In this paper the problem of nonparametric impulsive noise removal in multichannel images is addressed. The proposed filter class is based on the nonparametric estimation of the density probability function in a sliding filter window. The obtained results show good noise removal capabilities and excellent structure preserving properties of the new impulsive noise reduction technique.

Aiming at the weight degeneracy phenomena in particle filter algorithm, the improved particle filtering algorithm based on neural network was presented. BP neural network and generalized regression neural network (GRNN) are adapted to improve resampling algorithm and importance probability density function. This algorithm utilizes the nonlinear mapping function of BP neural network. First of al...

MOTIVATION The advent of high throughput data has led to a massive increase in the number of hypothesis tests conducted in many types of biological studies and a concomitant increase in stringency of significance thresholds. Filtering methods, which use independent information to eliminate less promising tests and thus reduce multiple testing, have been widely and successfully applied. However,...

The prefrontal cortex exerts top-down influences on several aspects of higher-order cognition by functioning as a filtering mechanism that biases bottom-up sensory information toward a response that is optimal in context. However, research also indicates that not all aspects of complex cognition benefit from prefrontal regulation. Here we review and synthesize this research with an emphasis on ...

the probability density functions fitting to the discrete probability functions has always been needed, and very important. this paper is fitting the continuous curves which are probability density functions to the binomial probability functions, negative binomial geometrics, poisson and hypergeometric. the main key in these fittings is the use of the derivative concept and common differential ...

This thesis addresses several challenges in Bayesian target tracking, particularly for array signal processing applications, and for multiple targets. The optimal method for multiple target tracking is the Bayes’ joint filter that operates by hypothesising all the targets collectively using a joint state. As a consequence, the computational complexity of the filter increases rapidly with the nu...

A new processor for detecting a radar target in correlated, non-Gaussian noise is obtained. When this processor and a matched filter are excited with this noise, performance is improved over that of the matched filter alone. The processor is obtained by developing an approximate, bivariate, probability density for the noise and constructing a Neyman-Pearson test and then using an approximation ...