Anomaly recognition has always been a prominent subject in preliminary geochemical explorations. Among the regional geochemical data processing, there are a range of statistical and data mining techniques as well as different mapping methods, which serve as presentations of the outputs. The outlier’s values are of interest in the investigations where data are gathered under controlled condition...

This paper reviews several periodogram-based methods for estimating the long-memory parameter H in time series and suggests a way to robustify them. The high frequencies tend to bias the estimates. Using only low frequencies eliminates the bias but increases the variance. We hence suggest plotting the estimates of H as a function of a parameter which balances bias versus variance and, if the pl...

We consider the combined completion of 3D surface relief and colour for the hidden and missing portions of objects captured with 2 1 2 D (or 3D) capture techniques. Through an extension of nonparametric texture synthesis to facilitate the completion of localised 3D surface structure (relief) over an underlying geometric surface completion we achieve realistic, plausible completion and extension...

Subject motion during the time course of functional activation studies has been shown to cause spurious signals which can mimic 'true' activation. Therefore, the importance of motion correction has been widely recognized. Correction with post-processing using image registration software is common practice in functional imaging and analysis. Many image registration algorithms, developed for anal...

Several autoregressive (AR) and autoregressive moving average (ARMA) parametric spectral estimators were evaluated for use in tissue strain estimation. Using both 1-D simulations and in vitro phantom experiments, the performance of these parametric spectral strain estimators were compared against both a nonparametric discrete Fourier transform (DFT) spectral strain estimator and a coherent elas...

Trajectory optimization of a controlled dynamical system is an essential part of autonomy, however many trajectory optimization techniques are limited by the fidelity of the underlying parametric model. In the field of robotics, a lack of model knowledge can be overcome with machine learning techniques, utilizing measurements to build a dynamical model from the data. This paper aims to take the...

Parallel computing has emerged as an environment for computing inherently parallel and computation intensive applications that requires huge processing power. Performance has always been a key factor in determining the success of parallel systems. Evaluating and analyzing the performance of parallel scheduling algorithms (i.e. parallel applications) is an important aspect of parallel computing ...

The problem to track time-varying properties of a signal is studied. The somewhat contradictory notion of \time-varying spectrum" and how to estimate the \current" spectrum in an on-line fashion is discussed. The traditional concepts and relations between time-and frequency resolution are crucial for this problem. As adaptive estimation algorithm is used to estimate the parameters of a time-var...

(a) Write down the probability distribution of x. Solution: p(x = 0|μ) = 1− μ, so p(x|μ) = μx(1− μ)1−x, this is known as the Bernoulli distribution. (b) Show that this is a proper probability distribution, i.e. the probability sum up to 1. What is the expectation and variance of this distribution? Solution: ∑ x∈{0,1} p(x|μ) = p(x = 0|μ) + p(x = 1|μ) = 1− μ+ μ = 1 E(x) = ∑ x∈{0,1} xp(x|μ) = 0× p...