Results 31 to 40 of about 38,728 (269)
Simulation-based inference for model parameterization on analog neuromorphic hardware
Neuromorphic Computing and Engineering, 2023 The BrainScaleS-2 (BSS-2) system implements physical models of neurons as well as synapses and aims for an energy-efficient and fast emulation of biological neurons.
Jakob Kaiser +4 more
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Application of Soft-Clustering to Assess Consciousness in a CLIS Patient
Brain Sciences, 2022 Completely locked-in (CLIS) patients are characterized by sufficiently intact cognitive functions, but a complete paralysis that prevents them to interact with their surroundings.
Sophie Adama, Martin Bogdan
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Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition [PDF]
, 2015 A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density.
Saxena, Vishal, Wu, Xinyu, Zhu, Kehan
core +3 more sources
Frontiers in Neuroscience, 2022 Earth orbit is a limited natural resource that hosts a vast range of vital space-based systems that support the international community's national, commercial and defence interests.
Nicholas Ralph +7 more
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The influence of astrocytic leaflet motility on ionic signalling and homeostasis at active synapses
Scientific Reports, 2023 Astrocytes display a highly complex, spongiform morphology, with their fine terminal processes (leaflets) exercising dynamic degrees of synaptic coverage, from touching and surrounding the synapse to being retracted from the synaptic region.
Marinus Toman +7 more
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Memristor Degradation Analysis Using Auxiliary Volt-Ampere Characteristics
Micromachines, 2022 The memristor is one of the modern microelectronics key devices. Due to the nanometer scale and complex processes physic, the development of memristor state study approaches faces limitations of classical methods to observe the processes.
Georgy Teplov +8 more
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Spiking Neural Networks for Inference and Learning: A Memristor-based Design Perspective [PDF]
, 2019 On metrics of density and power efficiency, neuromorphic technologies have the potential to surpass mainstream computing technologies in tasks where real-time functionality, adaptability, and autonomy are essential.
Abbott +56 more
core +2 more sources
Elements, 2022 In the face of increasingly large computational demands and the impending halt to Moore's law, the semiconductor industry has been forced to re-evaluate the traditional computing paradism. Central to this re-evaluation has been the novel development of neuromorphic computing - an approach that, at its core, seeks to replicate the brain in silicon ...
null Elements, Will Riherd
openaire +1 more source
Self-Organizing Multiple Readouts for Reservoir Computing
IEEE Access, 2023 With advancements in deep learning (DL), artificial intelligence (AI) technology has become an indispensable tool. However, the application of DL incurs significant computational costs, making it less viable for edge AI scenarios.
Yuichiro Tanaka, Hakaru Tamukoh
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Martingales and the fixation time of evolutionary graphs with arbitrary dimensionality
Royal Society Open Science, 2022 Evolutionary graph theory (EGT) investigates the Moran birth–death process constrained by graphs. Its two principal goals are to find the fixation probability and time for some initial population of mutants on the graph.
Travis Monk, André van Schaik
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