Neuromorphic computing could address the inherent limitations of conventional silicon
technology in dedicated machine learning applications. Recent work on silicon-based …

The brain exhibits extraordinary information processing capabilities thanks to neural
networks that can operate in parallel with minimal energy consumption. Memory and …

In this paper, the resistive switching and neuromorphic behaviour of memristive devices
based on parylene, a polymer both low-cost and safe for the human body, is …

Nowadays, neuromorphic systems based on memristors are considered promising
approaches to the hardware realization of artificial intelligence systems with efficient …

Neuromorphic systems consisting of artificial neurons and memristive synapses could
provide a much better performance and a significantly more energy-efficient approach to the …

An array of cross-point memristive devices has been implemented on the basis of yttria-
stabilized zirconia thin film for applications in prototypes of spiking neural networks. The …

Functional coupling live neurons through artificial synapses is the primary requirement for
their implementation as prosthetic devices or in building hybrid networks. Here, the first …

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

Parylene is a widely used polymer possessing such advantages as low cost and safety for
the human body. Recently, several studies have been conducted showing that parylene can …

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 …