Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Апрель 13, 2025

Abstract Neuromorphic computing aims to develop hardware platforms that emulate the effectiveness of our brain. In this context, brain-inspired self-organizing memristive networks have been demonstrated as promising physical substrates for in materia computing. However, understanding connection between network dynamics and information processing capabilities these systems still represents a challenge. work, we show neuromorphic nanowire behavior can be modeled an Ornstein-Uhlenbeck process which holistically combines stimuli-dependent deterministic trajectories stochastic effects. This unified modeling framework, able describe main features including noise jumps, enables investigation quantification roles played by on system context reservoir These results pave way development paradigms exploiting same platform similar what brain does.

Язык: Английский