This work proposes, implements and evaluates the FP-QIEA-R model as a new quantum inspired evolutionary algorithm based on the concept of quantum superposition that allows the optimization process to be carried on with a ...

The Evolutionary Algorithms have main features like: population, evolutionary operations (crossover, mate, mutation and others). Most of them are based on randomness and follow a criteria using fitness like selector. The ...

A model is developed to describe the electrostatic boundary layer in a positively biased magnetic filter in filtered arcs with low collisionality. The set of equations used includes the electron momentum equation, with an ...

There are many Evolutionary Algorithms which main features are: population, evolutionary operations (crossover, mate, mutation and others). Most of them are based on randomness and follow a criteria using fitness like ...

Tracking multiple objects is a challenging problem for an automated system, with applications in many domains. Typically the system must be able to represent the posterior distribution of the state of the targets, using a ...

In this dissertation we present techniques for filtering of tomographic projections with Poisson noise. For the filtering of the tomogram projections we use variations of three filtering techniques: Bayesian estimation, ...

This work presents a novel online early detector of high-volatility clusters based on uGARCH models (a variation of the GARCH model), risk-sensitive particle-filtering-based estimators, and hypothesis testing procedures. ...

Metallorganic molecules have been proposed as excellent spin filters in molecular spintronics because of the large spin polarization of their electronic structure. However, most of the studies involving spin transport have ...