First hybrid memory technology to support adaptive local training and inference of artificial neural networks unveiled.

A prototype chip combines Ferroelectric capacitor and memoristor to handle both learning and predicting data to run AI ...

Project demonstrated that it is possible to perform on-chip training with competitive accuracy, sidestepping the need for off ...

A single structure built in the metal layers of an IC can implement both machine learning and analogue AI inferencing, according to a French team led by Grenoble lab CEA-Leti – and the CMOS below can ...

Memristors, or “memory resistors,” are the leading candidate for replacing synapses in a neuromorphic (brain-like) computer.

Researchers at the University of Greifswald, International Iberian Nanotechnology Laboratory, Max Planck Institute for the ...

Innovative optoelectronic memristors enable efficient in-sensor edge computing, reducing latency and power consumption while ...

Negative differential resistance, sometimes called negative dynamic resistance (NDR), occurs when an increase in voltage ...

A new technical paper titled “An Ultra-Robust Memristor Based on Vertically Aligned Nanocomposite with Highly Defective ...

"This is the first time all four memristor types have been observed in a single device," said Professor Radha Boya, senior author of the study. "It shows the remarkable tunability of nanofluidic ...

Summary: Researchers have developed the first sort-in-memory hardware system capable of tackling complex, nonlinear sorting tasks without traditional comparators. Using a novel Digit Read mechanism ...

Abstract: Large-scale FFT operations in NR system are highly resource-intensive and computationally complicated, constituting a significant aspect of signal processing. Using high-radix to realize ...