In this study we describe a method for extending particle swarm optimization. We have presented a novel approach for avoiding premature convergence to local minima by the introduction of diversity in the swarm. The swarm is made more diverse and is encouraged to explore by employing a mechanism which allows each particle to use a different equation to update its velocity. This equation is also ...

Tracking an object's 3D position and orientation from a color image can been accomplished with particle filters if its color and shape properties are known. Unfortunately, initialization in particle filters is often manual or random, thus rendering the tracking recovery process slow or no longer autonomous. A method that uses image data to generate likely pose hypotheses for known objects is pr...

The scattering between Bragg reflections from nanocrystals is used to aid solution of the phase problem. We describe a method for reconstructing the charge density of a typical molecule within a single unit cell, if sufficiently finely-sampled "snap-shot" diffraction data (as provided a free-electron X-ray laser) are available from many nanocrystals of different sizes lying in random orientatio...

In most problems of sequential signal processing, measured or received data are processed in real time. Typically, the data are modeled by state-space models with linear or nonlinear unknowns and noise sources that are assumed either Gaussian or non-Gaussian. When the models describing the data are linear and the noise is Gaussian, the optimal solution is the renowned Kalman filter. For models ...

In this paper, we utilize the layer stripping method, a method used in seismology by geophysicists, to study a stochastic inverse problem arising from a one-dimensional Broadwell process. The Broadwell process can be described as a random walk of a particle that transitions, with a spatially dependent flip rate, between two states associated with the same speed but with different signs of veloc...

The particle swarm optimization (PSO), now widely used in the electromagnetics community, is a robust evolutionary method based on the property of swarm intelligence. This paper focuses on the random variable effect in the PSO algorithm, and two random distribution functions, namely, the uniform distribution and Gaussian distribution, are studied and compared in details. It is revealed through ...

We explore the gap-tooth method for multiscale modeling of systems represented by microscopic physics-based simulators, when coarse-grained evolution equations are not available in closed form. A biased random walk particle simulation, motivated by the viscous Burgers equation, serves as an example. We construct macro-to-micro (lifting) and micro-to-macro (restriction) operators, and drive the ...

In Monte Carlo (MC) simulations of semiconductor devices it is necessary to enhance the statistics in sparsely populated regions of interest. In this work the Monte Carlo method for stationary carrier transport, known as the Single-Particle MC method, is considered. It gives a solution to the stationary boundary value problem defined by the semi-classical Boltzmann equation (BE). Using a formal...

The distributed SLAM system has a similar estimation performance and requires only one-fifth of the computation time compared with centralized particle filter. However, particle impoverishment is inevitably because of the random particles prediction and resampling applied in generic particle filter, especially in SLAM problem that involves a large number of dimensions. In this paper, particle f...

Point scatterers are placed on the real line such that the distances between scatterers are independent identically distributed random variables (stationary renewal process). For a fixed configuration of scatterers a particle performs the following random walk: The particle starts at the point x with velocity v, Iv[ = 1. In between scatterers the particle moves freely. At a scatterer the partic...