Results 121 to 130 of about 1,253 (169)

Identification of preterm birth based on RQA analysis of electrohysterograms [PDF]

open access: possibleComputer Methods and Programs in Biomedicine, 2018
Common methods for data analysis are mainly based on linear concepts, but in recent years nonlinear dynamics methods have been introduced. It is a well-known fact that In typical biological systems lack of stationarity and rather sudden changes of state are the properties distinguishing them from each other. There is an urgent need to better understand
Piotr Laudanski   +2 more
exaly   +3 more sources

Epilepsy identification based on EEG signal using RQA method

Advances in Medical Sciences, 2019
Epilepsy is one of the most common neurological diseases and its cause is not unequivocal. Thus, additional methods and searches that may help to diagnose the disease are used in the clinical practice. In this study, we tested the possibility of using the Recurrence Quantification Analysis (RQA) method to identify epilepsy and present the analysis of ...
Marta Borowska   +2 more
exaly   +3 more sources

Detecting BGP instability using Recurrence Quantification Analysis (RQA)

2015 IEEE 34th International Performance Computing and Communications Conference (IPCCC), 2015
The Border Gateway Protocol (BGP) is the default Internet routing protocol that manages connectivity among Autonomous Systems (ASes). Although BGP disruptions are rare, when they occur the consequences can be very damaging. Consequently there has been considerable effort aimed at understanding what is normal and abnormal BGP traffic and, in so doing ...
Grenville Armitage, Bahaa Al-Musawi
exaly   +2 more sources

Detection of Transformer Cores Looseness Using RQA

2010 Asia-Pacific Power and Energy Engineering Conference, 2010
This paper proposes a recurrence qualification analysis (RQA) based method which is a useful tool to detect the subtle nonlinear changes in time series data to monitor the decreasing clamping forces of transformer iron cores. Firstly, suitable parameters including the distance threshold Â? for RQA are chosen according to the dynamical structures of the
Jie Guo   +4 more
exaly   +2 more sources

Classification of the surface EMG signal using RQA based representations

2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008
Feature extraction is a key element of pattern recognition for myoelectric control. In this paper, recurrence plots and recurrence quantification analysis (RQA) are used as the feature extractor for surface EMG signals. For eight different hand motions, two-channel EMG signals are recorded.
Xiangyang Zhu
exaly   +2 more sources

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