Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL)
techniques, which rely on networks of connected simple computing units operating in …

Data-intensive computing operations, such as training neural networks, are essential for
applications in artificial intelligence but are energy intensive. One solution is to develop …

For leveraging wearable technologies to advance precision medicine, personalized and
learning-based analysis of continuously acquired health data is indispensable, for which …

Gradient backpropagation (BP) requires symmetric feedforward and feedback connections—
the same weights must be used for forward and backward passes. This" weight transport …

Due to the complexity of real environments, it is hard to detect toxic and harmful gases by
sensors. To address such an issue, an artificial olfactory system is promoted, emulating the …

Nanomagnetic and spintronic devices, which make use of physical phenomena in materials
and interfaces like perpendicular magnetic anisotropy (PMA) and spin–orbit torque (SOT) to …

The human brain intrinsically operates with a large number of synapses, more than 1015.
Therefore, one of the most critical requirements for constructing artificial neural networks …

Memristor crossbar arrays carry out multiply-add operations in parallel in the analog domain,
and so can enable neuromorphic systems with high throughput at low energy and area …

Soft wearable strain sensors with mechanically invisible interactions with skin tissue have
enabled precise diagnosis and effective treatment of neurological movement disorders in a …

Emerging technologies have enabled efficient, high-speed realizations of ultra-dense
crossbar arrays, driving the need for better insight in the transient operation of such systems …