Results 51 to 60 of about 10,988 (267)
Hyperdimensional decoding of spiking neural networks
This work presents a novel spiking neural network (SNN) decoding method, combining SNNs with hyperdimensional computing (HDC). This decoding method is designed to achieve high accuracy, high noise robustness, low inference latency and low energy ...
Cedrick Kinavuidi +2 more
doaj +1 more source
Neuromorphic spintronics combines two advanced fields in technology, neuromorphic computing and spintronics, to create brain-inspired, efficient computing systems that leverage the unique properties of the electron's spin. In this book chapter, we first introduce both fields - neuromorphic computing and spintronics and then make a case for neuromorphic
Atreya Majumdar, Karin Everschor-Sitte
openaire +2 more sources
Monolithic UV‐ozone oxidation of Ta forms an ultrathin Ta2O5/TaOx bilayer enabling resistive switching with a vertical defect gradient. A stoichiometric surface layer over an oxygen‐deficient sublayer promotes localized filament nucleation near the top interface, enabling low‐voltage operation, and reduced cycle‐to‐cycle variability.
Seunghoon Yang +11 more
wiley +1 more source
Ferroelectric nematic liquid crystals (FNLCs) offer fast, tunable polarization and low‐voltage operation but suffer from poor polarization retention at zero field. Semiconductor‐modified FNLCs enhance polarization retention and exhibit short‐ and long‐term electro‐optical responses, while also supporting spike‐type signal integrations.
Kutay Sagdic, Weiming Yao, Danqing Liu
wiley +1 more source
Nanoscale Spatial Tuning of Superconductivity in Cuprate Thin Films via Direct Laser Writing
Maskless direct laser writing enables local control of oxygen stoichiometry in epitaxial YBCO thin films under ambient conditions. Sub‐micrometer grayscale patterns with tunable optical response and superconducting transport properties are achieved.
Irene Biancardi +11 more
wiley +1 more source
The more the merrier: running multiple neuromorphic components on-chip for robotic control
It has long been realized that neuromorphic hardware offers benefits for the domain of robotics such as low energy, low latency, as well as unique methods of learning.
Evan Eames +11 more
doaj +1 more source
Accelerated neuromorphic cybernetics [PDF]
Accelerated mixed-signal neuromorphic hardware refers to electronic systems that emulate electrophysiological aspects of biological nervous systems in analog voltages and currents in an accelerated manner. While the functional spectrum of these systems already includes many observed neuronal capabilities, such as learning or classification, some areas ...
openaire +3 more sources
Sodium alginate regulates interfacial ion transport and retention in electrolyte‐gated synaptic transistors. The carboxylate‐rich polymeric network forms a dynamic interfacial ion‐diffusion barrier that facilitates ion injection during programming while suppressing ion back‐diffusion, thereby stabilizing the electrochemically doped channel state.
Chaeyeon Han +6 more
wiley +1 more source
An interface‐defect co‐engineered strategy enables bias‐programmable integration of self‐powered photodetection and low‐power synaptic functionalities within a single‐material amorphous Ga2O3 device. This design achieves reversible switching via voltage modulation, supporting high‐contrast imaging and visual memory, and demonstrates a neuromorphic ...
Wanjun Li +13 more
wiley +1 more source
Neuromorphic motivated systems [PDF]
Although reinforcement learning has been extensively modeled, few agent models that incorporate values use biologically plausible neural networks as a uniform computational architecture. We call biologically plausible neural network architecture neuromorphic. This paper discusses some theoretical constraints on neuromorphic intrinsic value systems [3].
James C. Daly +2 more
openaire +1 more source

