Results 191 to 200 of about 215,411 (303)
Bio-plausible reconfigurable spiking neuron for neuromorphic computing. [PDF]
Xiao Y +16 more
europepmc +1 more source
An on‐demand ultra‐reconfigurable intelligent vision system with hierarchical reconfigurability from device to system levels is demonstrated. Through co‐design of a multi‐paradigm device, reconfigurable circuits, and adaptive system architecture/algorithms, the system enables seamless switching among spiking, non‐spiking, neuromorphic imaging (NI), and
Biyi Jiang +7 more
wiley +1 more source
Double-opponent spiking neuron array with orientation selectivity for encoding and spatial-chromatic processing. [PDF]
Li D +11 more
europepmc +1 more source
Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale +6 more
wiley +1 more source
A spiking neuron model of moral judgment in trolley dilemmas. [PDF]
Gothard T, Davies J.
europepmc +1 more source
A functional spiking-neuron model of activity-silent working memory in humans based on calcium-mediated short-term synaptic plasticity. [PDF]
Pals M +4 more
europepmc +1 more source
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang +14 more
wiley +1 more source
On Computing Boolean Functions by a Spiking Neuron
Computations by spiking neurons are performed using the timing of action potentials. We investigate the computational power of a simple model for such a spiking neuron in the Boolean domain by comparing it with traditional neuron models such as threshold
Michael Schmitt
core
Steep-Slope CuInP<sub>2</sub>S<sub>6</sub> Ferroionic Threshold Switching Field-Effect Transistor for Implementation of Artificial Spiking Neuron. [PDF]
Baek S +6 more
europepmc +1 more source
Ferroelectric Devices for In‐Memory and In‐Sensor Computing
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang +5 more
wiley +1 more source

