Results 21 to 30 of about 37,924 (271)
Martingales and the characteristic functions of absorption time on bipartite graphs
Royal Society Open Science, 2021 Evolutionary graph theory investigates how spatial constraints affect processes that model evolutionary selection, e.g. the Moran process. Its principal goals are to find the fixation probability and the conditional distributions of fixation time, and ...
Travis Monk, André van Schaik
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Neuromorphic Silicon Neuron Circuits [PDF]
Frontiers in Neuroscience, 2011 ISSN:1662 ...
Indiveri, Giacomo +19 more
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Toward Near-Real-Time Training With Semi-Random Deep Neural Networks and Tensor-Train Decomposition
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 In recent years, deep neural networks have shown to achieve state-of-the-art performance on several classification and prediction tasks. However, these networks demand undesirable lengthy training times coupled with high computational resources (memory ...
Humza Syed +3 more
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Frontiers in Neuromorphic Engineering [PDF]
Frontiers in Neuroscience, 2011 ISSN:1662 ...
Indiveri, G, Horiuchi, T K
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Neuromorphic Learning towards Nano Second Precision [PDF]
, 2013 Temporal coding is one approach to representing information in spiking neural networks. An example of its application is the location of sounds by barn owls that requires especially precise temporal coding. Dependent upon the azimuthal angle, the arrival
Meier, Karlheinz +3 more
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Energy-Efficient Neuromorphic Classifiers [PDF]
Neural Computation, 2016 Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. The energy consumptions promised by neuromorphic engineering are extremely low, comparable to those of ...
Martí, Daniel +3 more
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Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades [PDF]
, 2015 Creating datasets for Neuromorphic Vision is a challenging task. A lack of available recordings from Neuromorphic Vision sensors means that data must typically be recorded specifically for dataset creation rather than collecting and labelling existing ...
Ajinkya eJayawant +4 more
core +5 more sources
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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On-chip Few-shot Learning with Surrogate Gradient Descent on a Neuromorphic Processor [PDF]
, 2019 Recent work suggests that synaptic plasticity dynamics in biological models of neurons and neuromorphic hardware are compatible with gradient-based learning (Neftci et al., 2019).
Neftci, Emre +3 more
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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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