3 papers
cs.LG2026
Neuronal Self-Adaptation Enhances Capacity and Robustness of Representation in Spiking Neural Networks
Zhuobin Yang, Yeyao Bao, Liangfu Lv +3
Spiking Neural Networks (SNNs) are promising for energy-efficient, real-time edge computing, yet their performance is often constrained by the limited adaptability of conventional…
physics.app-ph2024
Self-reconfigurable Multifunctional Memristive Nociceptor for Intelligent Robotics
Shengbo Wang, Mingchao Fang, Lekai Song +5
Artificial nociceptors, mimicking human-like stimuli perception, are of significance for intelligent robotics to work in hazardous and dynamic scenarios. One of the most essential…
physics.app-ph2024
Real-Time State Modulation and Acquisition Circuit in Neuromorphic Memristive Systems
Shengbo Wang, Cong Li, Tongming Pu +5
Memristive neuromorphic systems are designed to emulate human perception and cognition, where the memristor states represent essential historical information to perform both low-le…