TL;DR
This work constructs a novel two-dimensional discrete fractional-order chaotic map and establishes a corresponding TDF-TDR framework with the proposed map as the driving module, and deduces the complete mathematical formulation and conducts systematic dynamical analysis.
This work demonstrates that the NMSE from an RC-based prediction model can be used as an indicator for system dynamical characterization, and provides an alternative approach for probing dynamical regimes from finite time series, paving the way for embedded neuromorphic tools dedicated to the experimental analysis of c...
Four-dimensional chaotic systems have garnered significant attention due to their complex nonlinear dynamics, high-dimensional complexity, and wide range of applications in science and engineering. This paper proposes and investigates a novel four-dimensional chaotic system in both constant- and variable-order framewor...
Reliable finite-horizon forecasting of chaotic dynamics is challenging because small approximation errors grow rapidly during recursive prediction. This study presents a controlled comparison of data-driven and physics-regularized forecasting methods for the Lorenz and Rössler systems. The proposed Hybrid Physics-Infor...
In this study, we develop a novel variable-order fractional extension of an eight-dimensional (8D) hyperchaotic differential equation system modeled via the Liouville–Caputo operator. Moving beyond constant fractional-order models, our system implements time-variable orders, which enable its historical memory structure...
This work explores the finite-time synchronization (FTS) problem of fractional-order fuzzy cellular neural networks (FOFCNNs) that comprise mixed time-varying delays (TVDs) and interaction terms, and utilizes the Lyapunov stability theory with the QMSDC technique and finite time (FT) stability theory to guarantee the s...
This study investigates the capability of deep neural networks to infer the time-evolution of the Rössler system a canonical chaotic oscillator by leveraging initial conditions and forcing parameters as input variables and underscores the need for hybrid approaches to address long-term instability.
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