6 papers
Emergence of solitary and chimera states in adaptive pendulum networks under diverse learning rules
R. Anand, V. K. Chandrasekar, R. Suresh
We investigate the interplay between phase lag and adaptive learning rules in a network of identical pendulum oscillators, where the coupling strengths evolve dynamically in respon…
Frustration-Induced Collective Dynamical States in Pulse-Coupled Adaptive Winfree Networks
R. Anand, V. K. Chandrasekar, R. Suresh
We investigate collective dynamics in a pulse-coupled adaptive Winfree network under the influence of a frustration (phase-lag) parameter. The coupling strengths coevolve according…
Multivariate time series prediction using clustered echo state network
S. Hariharan, R. Suresh, V. K. Chandrasekar
Many natural and physical processes can be understood by analyzing multiple system variables evolving, forming a multivariate time series. Predicting such time series is challengin…
Heterogeneous noise-induced extreme events and synchronization in a globally coupled network of FitzHugh-Nagumo oscillators
S. Hariharan, R. Suresh, V. K. Chandrasekar
This study investigates the dynamics of a globally coupled network of heterogeneous FitzHugh Nagumo (FHN) oscillators under stochastic influences, with particular emphasis on the e…
Noise induced extreme events in single Fitzhugh-Nagumo oscillator
S. Hariharan, R. Suresh, V. K. Chandrasekar
The FitzHugh-Nagumo (FHN) model serves as a fundamental neuronal model which is extensively studied across various dynamical scenarios, we explore the dynamics of a scalar FHN osci…
Extreme events in the Lienard system with asymmetric potential: An in-depth exploration
B. Kaviya, R. Suresh, V. K. Chandrasekar
This research investigates the dynamics of a forced Lienard oscillator featuring asymmetric potential wells. We provide compelling evidence of extreme events (EE) in the system by…