73 citations · 370 across the 21 of their papers we have counts for
8 papers · 1 filter
Degree weighted recurrence networks for the analysis of time series data
Rinku Jacob, K. P. Harikrishnan, R. Misra +1
Recurrence networks are powerful tools used effectively in the nonlinear analysis of time series data. The analysis in this context is done mostly with unweighted and undirected co…
Is a hyperchaotic attractor superposition of two multifractals?
K. P. Harikrishnan, R. Misra, G. Ambika
In the context of chaotic dynamical systems with exponential divergence of nearby trajectories in phase space, hyperchaos is defined as a state where there is divergence or stretch…
Can recurrence networks show small world property?
Rinku Jacob, K. P. Harikrishnan, R. Misra +1
Recurrence networks are complex networks, constructed from time series data, having several practical applications. Though their properties when constructed with the threshold valu…
Uniform framework for the recurrence-network analysis of chaotic time series
Rinku Jacob, K. P. Harikrishnan, R. Misra +1
We propose a general method for the construction and analysis of unweighted - recurrence networks from chaotic time series. The selection of the critical threshold in our…
Computing the multifractal spectrum from time series: An algorithmic approach
K. P. Harikrishnan, R. Misra, G. Ambika +1
We show that the existing methods for computing the f(α) spectrum from a time series can be improved by using a new algorithmic scheme. The scheme relies on the basic idea that the…
Parametric characterisation of a chaotic attractor using two scale Cantor measure
K P Harikrishnan, R Misra, G Ambika +1
A chaotic attractor is usually characterised by its multifractal spectrum which gives a geometric measure of its complexity. Here we present a characterisation using a minimal set…
Stochastic resonance as a filter for signal detection from multisignal inputs
K P Harikrishnan, G Ambika
We undertake a detailed numerical study of the phenomenon of stochastic resonance with multisignal inputs. A bistable cubic map is used as the model and we show that it combines th…
A non subjective approach to the GP algorithm for analysing noisy time series
K. P. Harikrishnan, R. Misra, G. Ambika +1
We present an adaptation of the standard Grassberger-Proccacia (GP) algorithm for estimating the Correlation Dimension of a time series in a non subjective manner. The validity and…