Means produced by distances

Distances of Time Series Components by Means of Symbolic Dynamics

In this note we describe a simple method for visualizing time-dependent similarities and dissimilarities between the components of a high-dimensional time series. On the base of symbolic dynamics, the time series is turned into a series of matrices whose rows quantify pattern types in the components of the original series. For different scales we introduce distances between the components via t...

Super–conducting niobium films produced by means of UHV arc

The paper shows that high–quality super-conducting Nb films can be deposited by means of arc discharges under ultra–high vacuum conditions. The critical temperature Tc of Nb–films obtained with a planar cathodic arc Ultra High Vacuum (UHV) system, is very close to that of pure bulk niobium Tc = 9.26 K and the transition to super–conducting state is very narrow. The films have higher Residual Re...

Artificial Fever Produced by Physical Means: Its Development and Application

SAR Image Despeckling Algorithms using Stochastic Distances and Nonlocal Means

This paper presents two approaches for filter design based on stochastic distances for intensity speckle reduction. A window is defined around each pixel, overlapping samples are compared and only those which pass a goodness-of-fit test are used to compute the filtered value. The tests stem from stochastic divergences within the Information Theory framework. The technique is applied to intensit...

Fuzzy C-Means Algorithm Based on Standard Mahalanobis Distances

Some of the well-known fuzzy clustering algorithms are based on Euclidean distance function, which can only be used to detect spherical structural clusters. Gustafson-Kessel clustering algorithm and Gath-Geva clustering algorithm were developed to detect non-spherical structural clusters. However, the former needs added constraint of fuzzy covariance matrix, the later can only be used for the d...