Results 31 to 40 of about 37,924 (271)
Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor [PDF]
, 2018 Neuromorphic computing is a new paradigm for design of both the computing hardware and algorithms inspired by biological neural networks. The event-based nature and the inherent parallelism make neuromorphic computing a promising paradigm for building ...
Glatz, Sebastian +4 more
core +1 more source
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
doaj +1 more source
SVITE: A Spike-Based VITE Neuro-Inspired Robot Controller [PDF]
, 2013 This paper presents an implementation of a neuro-inspired algorithm called VITE (Vector Integration To End Point) in FPGA in the spikes domain. VITE aims to generate a non-planned trajectory for reaching tasks in robots. The algorithm has been adapted
Domínguez Morales, Manuel Jesús +4 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
doaj +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
doaj +1 more source
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
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
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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A geographically distributed bio-hybrid neural network with memristive plasticity [PDF]
, 2017 Throughout evolution the brain has mastered the art of processing real-world inputs through networks of interlinked spiking neurons. Synapses have emerged as key elements that, owing to their plasticity, are merging neuron-to-neuron signalling with ...
Corna, Andrea +10 more
core +1 more source