Heart rate variability (HRV) analysis can be successfully applied to automatic classification of cardiac rhythm abnormalities. This paper presents a novel Java-based computer framework for feature extraction from cardiac rhythms. The framework called HRVFrame implements more than 30 HRV linear time domain, frequency domain, time-frequency domain, and nonlinear features. Output of the framework ...

drought monitoring, which is a crucial component of drought management, aims to provide information that enables and supports people and organizations to take actions to reduce potential drought-related impact and damage. we usually tend to focus on drought when it is occurring and to react when crises strike. however, recent experiences and developments on drought knowledge are encouraging soc...

Based on empirical financial time-series, we show that the ”silence-breaking” probability follows a super-universal power law: the probability of observing a large movement is inversely proportional to the length of the ongoing low-variability period. Such a scaling law has been previously predicted theoretically [1], assuming that the length-distribution of the low-variability periods follows ...

Using a time series framework, the paper studies the interactions of the annual real per capita GDP data of the G7 countries. We find evidence of six common nonstationary processes behind the international output dynamics. In addition, there is evidence for the existence of a common business cycle among these countries. The trend and cycle components of each output series are obtained with a pr...

temperature and precipitation are among important atmospheric parameters for watershed planning. assessment of temperature and precipitation trends is very important for future watershed planning. in this paper, trends of atmospheric parameters such as seasonal and annual temperature and precipitation were examined for the synoptic stations of bandar anzali, rasht, ramsar, babolsar and gorgan. ...

This paper presents a newmethod for robust online variability extraction in time series. The proposed estimator is simultaneously highly robust and efficient.We derive its breakdown point, influence function, and asymptotic variance and study the finite sample properties in a simulation study. © 2009 Elsevier B.V. All rights reserved.