arXiv subjects

R. B. Govindan

Publications and source records attributed to R. B. Govindan.

6 recordsLinked to original sources

arXiv2006

Comment on Wavelet Analysis and scaling properties of time series

In a recent work Manimaran et al. [Manimaran et al., Phys. Rev. E 72, 046120 (2005)] propose to use multiresolution Daubechies (DB) wavelets to (detrend) remove the low frequency trends and subsequently to quantify the multifractal structure in a given time series. In this comment, by applying DB wavelets to the long range correlated data we show that in the presence of linear trends, the wavelets could not able to distinguish the correlations from trends. As the DB wavelets based detrending will not be able to quantify the correlations masked by trends, its multifractal extension can not always yield a correct estimate of the multifractal spectrum of the given data.

physics.data-an↗

arXiv2005

Appropriateness of correlated first order auto-regressive processes for modeling daily temperature records

The present study investigates linear and volatile (nonlinear) correlations of first-order autoregressive process with uncorrelated AR (1) and long-range correlated CAR (1) Gaussian innovations as a function of the process parameter ($θ$). In the light of recent findings \cite{jano}, we discuss the choice of CAR (1) in modeling daily temperature records. We demonstrate that while CAR (1) is able to capture linear correlations it is unable to capture nonlinear (volatile) correlations in daily temperature records.

physics.ao-ph↗

arXiv2005

Time delay and partial coherence analyses to identify cortical connectivities

Recently it has been demonstrated by Albo that partial coherence analysis is sensitive to signal to noise ratio (SNR) and that it will always identify the signal with the highest SNR among the three signals as the main (driving) influence. We propose to use time delay analysis in parallel to partial coherence analysis to identify the connectivities between the multivariate time series. Both are applied to a theoretical model (used by Albo) to analyse the connections introduced in the model. Time delay analysis identifies the connections correctly. We also apply these analyses to the electroencephalogram (EEG) and electromyogram (EMG) of essential tremor patients and EEG of normal subjects while bimanually tapping their index fingers. Biologically plausible cortico-muscular and cortico-cortical connections are identified by these methods.

physics.med-ph↗

arXiv2004

Estimation of time delay by coherence analysis

Using coherence analysis (which is an extensively used method to study the correlations in frequency domain, between two simultaneously measured signals) we estimate the time delay between two signals. This method is suitable for time delay estimation of narrow band coherence signals for which the conventional methods cannot be reliably applied. We show by analysing coupled Rössler attractors with a known delay, that the method yields satisfactory results. Then, we apply this method to human pathologic tremor. The delay between simultaneously measured traces of Electroencephalogram (EEG) and Electromyogram (EMG) data of subjects with essential hand tremor is calculated. We find that there is a delay of 11-27 milli-seconds ($ms$) between the tremor correlated parts (cortex) of the brain (EEG) and the trembling hand (EMG) which is in agreement with the experimentally observed delay value of 15 $ms$ for the cortico-muscular conduction time. By surrogate analysis we calculate error-bars of the estimated delay.

physics.data-an↗

arXiv2002

Volatility in atmospheric temperature variability

Using detrended fluctuation analysis (DFA), we study the scaling properties of the volatility time series $V_i=| T_{i+1}-T_i|$ of daily temperatures $T_i$ for ten chosen sites around the globe. We find that the volatility is long range power-law correlated with an e xponent $γ$ close to 0.8 for all sites considered here. We use this result to test the scaling performance of several state-of-the art global climate models and find that the models do not reproduce the observed scaling behavior.

cond-mat.stat-mech↗

arXiv2002

Global climate models violate scaling of the observed atmospheric variability

We test the scaling performance of seven leading global climate models by using detrended fluctuation analysis. We analyse temperature records of six representative sites around the globe simulated by the models, for two different scenarios: (i) with greenhouse gas forcing only and (ii) with greenhouse gas plus aerosol forcing. We find that the simulated records for both scenarios fail to reproduce the universal scaling behavior of the observed records, and display wide performance differences. The deviations from the scaling behavior are more pronounced in the first scenario, where also the trends are clearly overestimated.

cond-mat.stat-mech↗