Memristive devices, known for their nonvolatile resistive switching, are promising
components for next-generation neuromorphic computing systems, which mimic the brain's …

Memristors are promising candidates for synapse emulation in brain-inspired neuromorphic
computing systems. The main obstacle to their usage in such systems is high variability of …

Currently, there is growing interest in wearable and biocompatible smart computing and
information processing systems that are safe for the human body. Memristive devices are …

Parylene is a widely used polymer possessing advantages such as simple and cheap
production, possibility of fabrication on flexible substrates, transparency, and safety for the …

Neuromorphic networks adopt human brain mechanisms and create a promising way to
solve various artificial cognitive problems. Memristors, novel circuit design elements, could …

Resistive random-access memory (RRAM) has been explored to implement neuromorphic
systems to accelerate neural networks. In this study, an RRAM crossbar array using …

From the very beginning, the emulation of biological principles has been the primary avenue
for the development of energy-efficient artificial intelligence systems. Reservoir computing …

Memristive devices have proven themselves as synaptic elements with rich internal
dynamics and stochasticity for bio-inspired neuromorphic computing systems. Memristors …

In this work, thin films of hafnium oxide HfO x obtained by electron beam deposition were
crystallized by thermal annealing in air atmosphere. The relationship between the structural …

The central pattern generator (CPG) is one of the key elements of the nervous system of
Vertebrates, determining the motor, breathing, swallowing, etc. cyclic motor patterns of a …