Computing with spiking neuron networks. In Handbook of natural computing, pages 335-376. Springer, 2012.Paugam-Moisy, H.; Bohte, S.M. Computing with spiking neuron networks. In Handbook of Natural Computing; Springer: Berlin, Germany, 2012....
Computing with spiking neuron networks 2012, Handbook of Natural Computing View all citing articles on ScopusHélène Paugam-Moisy obtained the French degree Agrégation de Mathématiques in 1987 and she received a Ph.D. in Computer Science in 1992 at University Lyon 1 and Ecole Normale Supérieur...
In the context of spiking neurons, the term “potential” means (loosely) electrical voltage rather than “possible” or “impending.” The demo program simulates 16 time ticks. At each tick, the three input 0 or 1 values are displayed along with the state of the neuron (active or ...
This work explores recent hardware designs focusing on perspective applications (like convolutional neural networks) for both neuron types from the energy efficiency side to analyse whether there is a possibility for spiking neuromorphic hardware to grow up for a wider use. Our comparison shows that ...
The most existing dynamics and learning paradigms for spiking neurons with a common Leaky Integrate-and-Fire (LIF) neuron model often result in relatively ... R Xiao,Z Hu,J Zhang,... - 《Neurocomputing》 被引量: 0发表: 2025年 Early vision and attention Paradigms for Computing with Spiking...
They consist of a memoryless readout neuron that is trained on top of a randomly connected recurrent neural network. RC systems are commonly used in two flavors: with analog or binary (spiking) neurons in the recurrent circuits. ... L Büsing,B Schrauwen,R Legenstein 被引量: 10发表: 2013...
High-performance deep spiking neural networks with 0.3 spikes per neuron To address challenges of training spiking neural networks (SNNs) at scale, the authors propose a scalable, approximation-free training method for deep SNNs using time-to-first-spike coding. They demonstrate enhanced performance...
Metal-organic framework single crystal for in-memory neuromorphic computing with a light control Semyon V. Bachinin Alexandr Marunchenko Valentin A. Milichko Communications Materials(2024) High-performance deep spiking neural networks with 0.3 spikes per neuron ...
I demonstrate that simple synchrony-based neuron models can extract these useful features, by using spiking models in several sensory modalities. 展开 关键词: aggregate compression living tissues rheology elasto-visco-plasticity DOI: 10.1371/journal.pcbi.1002561 被引量: 131 ...
the Mosaic is fully compatible with standard integrated RRAM/CMOS processes available at the foundries, without the need for extra post-processing steps. Specifically, we have designed the Mosaic for small-world Spiking Neural Networks (SNNs), where the communication between the tiles is through elec...