Seoul National University

Artificial neural networks

Spiking Neural Networks Offer Promising Solutions for Real-Time Time-Series Data Processing

Research conducted at Seoul National University of Science & Technology has found that Spiking Neural Networks (SNNs) can efficiently process time-series data by emulating biological neuronal dynamics. The study proposed a novel encoding method, Filtered Temporal-Population (FTP), which captures temporal and spatial correlations within data segments, making it suitable for

Seoul National University

Electrical Control of Topological 3Q State in Intercalated Van Der Waals Antiferromagnet CoTaS2

Research at Seoul National University has successfully demonstrated the electrical control of the topological 3Q state in the intercalated van der Waals antiferromagnet CoTaS2. The study, published in Nature Communications, employed ionic gating to manipulate the phase of the material, revealing a previously inaccessible phase space. This groundbreaking research offers