The emergence of artificial intelligence has represented great potential in solving a wide
range of complex problems. However, traditional general-purpose chips based on von …

Spiking Neural Networks (SNNs) have garnered substantial attention in brain-like computing
for their biological fidelity and the capacity to execute energy-efficient spike-driven …

With the rapid advances of artificial intelligence and its applications, the design of memristor-
based neuromorphic chips inspired by the human brain has become an important area of …

Recent advancements in neuromorphic computing have led to the development of hardware
architectures inspired by Spiking Neural Networks (SNNs) to emulate the efficiency and …

Auto-encoders are capable of performing input reconstruction, denoising, and classification
through an encoder-decoder structure. Spiking Auto-Encoders (SAEs) can utilize …

This article presents an efficient S‐parameter extraction method for memristor‐based
crossbar array circuits. The proposed approach involves converting the array into an …

Purpose. Studying the possibility of implementing a data classification method based on a
spiking neural network, which has a low number of connections and is trained based on …

Purpose. Studying the possibility of implementing a data classification method based on a
spiking neural network, which has a low number of connections and is trained based on …