The last decade has witnessed a number of important and exciting developments that had
been achieved for improving recurrence plot-based data analysis and to widen its …

Discretizing a nonlinear time series enables us to calculate its statistics fast and rigorously.
Before the turn of the century, the approach using partitions was dominant. In the last two …

We experimentally conduct an early detection of thermoacoustic instability in a staged single-
sector combustor using a novel methodology that combines symbolic dynamics and …

The analysis of event time series is in general challenging. Most time series analysis tools
are limited for the analysis of this kind of data. Recurrence analysis, a powerful concept from …

We study the effect of gravity on the synchronization of two coupled buoyancy-induced
turbulent flames by recurrence-based analysis and machine learning. A significant change …

Nonlinear dynamical systems often generate significant amounts of observational data such
as time series, as well as high-dimensional spatial data. To delineate recurrence dynamics …

We analyze the time series obtained from different dynamical regimes of evolving maps and
flows by constructing their equivalent time series networks, using the visibility algorithm. The …

We attempt to identify the driving region of combustion oscillations by methodologies based
on symbolic dynamics, synchronization, and complex networks. As the equivalence ratio is …

We study the feedback coupling of thermoacoustic combustion instability from the viewpoint
of a complex-systems approach, including the early detection of combustion instability. An …

In chemical industries, multiphase flows in a bubble column reactor are frequently observed.
The nonlinearity associated with bubble hydrodynamics, such as bubble–bubble and …