The memristor has recently demonstrated considerable potential in the field of large‐scale
data information processing. Metal halide perovskites (MHPs) have emerged as the leading …

Among many artificial neural networks, the research on Spike Neural Network (SNN), which
mimics the energy-efficient signal system in the brain, is drawing much attention. Memristor …

Bio-inspired hardware-based spiking neural networks (SNNs) has been suggested as a
promising computing system with low power consumption and parallel operation. We …

In this work, nanoscale wedge-structured silicon nitride (SiN x)-based resistive-switching
random-access memory with data non-volatility and conductance graduality has been …

The homeostatic neuron circuit using a double-gate MOSFET is proposed to imitate a
homeostasis functionality of a biological neuron in spiking neural networks (SNN) based on …

We analyze that the initial synaptic weight distribution affects the performance, such as the
learning speed, recognition rate and the power consumption in the spiking neural networks …

Brain-inspired analog neuromorphic systems based on the synaptic arrays have attracted
large attention due to low-power computing. Spike-timing-dependent plasticity (STDP) …

Background. Infrasound is a major threat to global health by causing injuries of the central
nervous system (CNS). However, there remains no effective therapeutic agent for preventing …

Recent advancements in artificial intelligence (AI) have profoundly impacted our daily lives
as well as various scientific fields. One of the core AI technologies is spiking neural networks …

Background. Infrasound is a major threat to global health by causing injuries of the central
nervous system (CNS). However, there remains no effective therapeutic agent for preventing …