Owing to its close resemblance to biological systems and materials, soft matter has been
successfully implemented in numerous bioelectronic and biosensing applications, as well as …

The unique electron spin, transfer, polarization and magnetoelectric coupling characteristics
of ABO3 multiferroic perovskite materials make them promising candidates for application in …

The memristor is a resistive switch where its resistive state is programable based on the
applied voltage or current. Memristive devices are thus capable of storing and computing …

We investigate the constructive role of an external noise signal, in the form of a low-rate
Poisson sequence of pulses supplied to all inputs of a spiking neural network, consisting in …

Here we provide a perspective concept of neurohybrid memristive chip based on the
combination of living neural networks cultivated in microfluidic/microelectrode system, metal …

This work is aimed to study experimental and theoretical approaches for searching effective
local training rules for unsupervised pattern recognition by high-performance memristor …

Neuromorphic computing has been extensively studied to mimic the brain functions of
perception, learning, and memory because it may overcome the von Neumann bottleneck …

Humanoid robots, intelligent machines resembling the human body in shape and functions,
cannot only replace humans to complete services and dangerous tasks but also deepen the …

Development of spiking neural networks (SNNs) controlling mobile robots is one of the
modern challenges in computational neuroscience and artificial intelligence. Such networks …

Resistive switching (RS) devices are metal/insulator/metal cells that can change their
electrical resistance when electrical stimuli are applied between the electrodes, and they …