arXiv subjects

K. Urbanowicz

Publications and source records attributed to K. Urbanowicz.

3 recordsLinked to original sources

arXiv2007

How random is your heart beat?

We measure the content of random uncorrelated noise in heart rate variability using a general method of noise level estimation using a coarse grained entropy. We show that usually - except for atrial fibrillation - the level of such noise is within 5 - 15% of the variance of the data and that the variability due to the linearly correlated processes is dominant in all cases analysed but atrial fibrillation. The nonlinear deterministic content of heart rate variability remains significant and may not be ignored.

physics.med-ph↗

arXiv2003

Combustion Process in a Spark Ignition Engine: Dynamics and Noise Level Estimation

We analyse the experimental time series of internal pressure in a four cylinder spark ignition engine. In our experiment, performed for different spark advance angles, apart from usual cyclic changes of engine pressure we observed oscillations. These oscillations are with longer time scales ranging from one to several hundred engine cycles depending on engine working conditions. Basing on the pressure time dependence we have calculated the heat released per cycle. Using the time series of heat release to calculate the correlation coarse-grained entropy we estimated the noise level for internal combustion process. Our results show that for a smaller spark advance angle the system is more deterministic.

nlin.CD↗

arXiv2003

Noise level estimation of time series using coarse grained entropy

We present a method of noise level estimation that is valid even for high noise levels. The method makes use of the functional dependence of coarse grained correlation entropy $K_2(\eps)$ on the threshold parameter $\eps$. We show that the function $K_2(\eps)$ depends in a characteristic way on the noise standard deviation $σ$. It follows that observing $K_2(\eps)$ one can estimate the noise level $σ$. Although the theory has been developed for the gaussian noise added to the observed variable we have checked numerically that the method is also valid for the uniform noise distribution and for the case of Langevine equation corresponding to the dynamical noise. We have verified the validity of our method by applying it to estimate the noise level in several chaotic systems and in the Chua electronic circuit contaminated by noise.

cond-mat.stat-mech↗