This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...

In searching a market-neutral arbitrage strategy in forex market, we took a portfolio of three major currency pairs, EUR-USD, USD-JPY, and EUR-JPY. There are eight approaches, different cases of short and long positions; for example buying 1st and selling two others, etc. Historical daily FX rates were gathered since January 1990 until February 2011. Monthly covariances between daily growth rat...

Genetically correlated traits do not evolve independently, and the covariances between traits affect the rate at which a population adapts to a specified selection regime. To measure the impact of genetic covariances on the rate of adaptation, we compare the rate fitness increases given the observed G matrix to the expected rate if all the covariances in the G matrix are set to zero. Using data...

A numerical method is developed for accurately approximating head and ̄ux covariances and cross-covariances in ®nite twoand three-dimensional domains using the mixed ®nite element method. The method is useful for determining head and ̄ux covariances for non-stationary ̄ow ®elds, for example those induced by injection or extraction wells, impermeable subsurface barriers, or non-stationary hydraulic...

Hepatitis B virus (HBV) is one of the most common DNA viruses that can cause aggressive hepatitis, cirrhosis and hepatocellular carcinoma. Although many people are persistently infected with HBV, the kinetics in serum levels of viral loads and the host immune responses vary from person to person. HBV precore/core open reading frame (ORF) encoding proteins, hepatitis B e antigen (HBeAg) and core...

In brain computer interface based on motor imagery, covariances matrices are widely used through spatial filters computation and other signal processing methods. Covariances matrices lie in the space of Semi-definite Positives (SPD) matrices and therefore, fall within the Riemannian geometry domain. Using a differential geometry frameworks, we propose different algorithms in order to classify c...

The Kalman filter requires knowledge about the noise statistics. In practical applications, however, the noise covariances are generally not known. In this paper, a method for estimating noise covariances from process data has been investigated. This method yields least-squares estimates of the noise covariances, which can be used to compute the Kalman filter gain.

methods for estimating the means and covariances of stumpage prices and incorporating _._ th m in harvest scheduling models. We approached the esti ation problem by fitting timeseries models to loblolly pine sawtimber and pulpwood stumpage prices in Georgia, USA, _= and deriving formulas for means and covariances of price predictions. Statistical evidence _ supported integrated autoregressive m...