A new kind of memristor mimics how the brain learns by combining analog and digital behavior, offering a promising solution ...

AlexNet is an artificial neural network created to recognize the contents of photographic images. It was developed in 2012 by then University of Toronto graduate ...

It was the shot heard 'round the world - a neural network that finally fulfilled decades of theoretical promise.

It was the shot heard 'round the world - a neural network that finally fulfilled decades of theoretical promise.

Memristors consume extremely little power and behave similarly to brain cells. Researchers from Jülich have now introduced ...

An openly available generative AI tool can interpret millions of cells in human tissues in hours, revealing new insights and allowing researchers and clinicians to ask questions about conditions such ...

Researchers have mapped the long-range synaptic connections involved in vocal learning in zebra finches, uncovering new ...

Spiking neural networks (SNNs) offer a promising energy-efficient alternative to artificial neural networks (ANNs), in virtue of their high biological plausibility, rich spatial-temporal dynamics, and ...

This paper presents a novel CFO self-compensating neural network. A CFO compensation module is designed ... it can be applied to all modulation schemes that are demodulable using constellation ...

Institute of Automation and Control Processes, Far Eastern Branch, Russian Academy of Science, 5 Radio Str, Vladivostok 690041, Russia ...

A) Schematic representation of the recorded area ... To this end, we constructed a spiking neural network model comprising randomly and sparsely connected excitatory and inhibitory neurons while ...