Stochastic dynamics and nonlinear systems form a critical nexus in modern science, where random processes intersect with complex, often non‐proportional responses. This field characterises phenomena ...

Engineers at Tokyo Institute of Technology (Tokyo Tech) have demonstrated a simple computational approach for supporting the classification performance of neural networks operating on sensor time ...

Non-linear physics is the study of systems where the output is not directly proportional to the input. Unlike linear systems, which follow simple, predictable relationships, non-linear systems exhibit ...

Complex network theory has become a key analytical framework in modern physics for studying structure, dynamics, and emergent behaviour in complex systems.

Efficient Large Displacement/Large Rotation Dynamic Simulations Using Nonlinear Dynamic Substructures Utilizing reduced-order dynamic math models (DMM) in linear system-level dynamic analyses is a ...

Highly reduced order models with nonlinear contact – extremely efficient computation. Modeled as linear components interconnected with highly reduced-order components. 1-linear reduced model, ...