Classification of multivariate data with a spiking neural network on neuromorphic hardware
نویسندگان
چکیده
منابع مشابه
A neuromorphic network for generic multivariate data classification.
Computational neuroscience has uncovered a number of computational principles used by nervous systems. At the same time, neuromorphic hardware has matured to a state where fast silicon implementations of complex neural networks have become feasible. En route to future technical applications of neuromorphic computing the current challenge lies in the identification and implementation of function...
متن کاملCommunity detection with spiking neural networks for neuromorphic hardware
We present results related to the performance of an algorithm for community detection which incorporates event-driven computation. We dene a mapping which takes a graph G to a system of spiking neurons. Using a fully connected spiking neuron system, with both inhibitory and excitatory synaptic connections, the ring paerns of neurons within the same community can be distinguished from ring p...
متن کاملUsing Games to Embody Spiking Neural Networks for Neuromorphic Hardware
Adding value to action-selection through reinforcement-learning provides a mechanism for modifying future decisions of real and artificial entities. This behavioral-level modulation is vital for performing in complex and dynamic environments. In this paper we focus on three classes of biologically inspired feed-forward spiking neural networks capable of action-selection via reinforcement-learni...
متن کاملThe effect of heterogeneity on decorrelation mechanisms in spiking neural networks: a neuromorphic-hardware study
Thomas Pfeil†,1, ∗ Jakob Jordan,2, ∗ Tom Tetzlaff,2 Andreas Grübl,1 Johannes Schemmel,1 Markus Diesmann,2, 3, 4 and Karlheinz Meier1 Kirchhoff-Institute for Physics, Heidelberg University, Heidelberg, Germany Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I, Jülich Research Centre, Jülich, Germany Department of Psychiatry, P...
متن کاملTraining Spiking Deep Networks for Neuromorphic Hardware
We describe a method to train spiking deep networks that can be run using leaky integrate-and-fire (LIF) neurons, achieving state-of-the-art results for spiking LIF networks on five datasets, including the large ImageNet ILSVRC-2012 benchmark. Our method for transforming deep artificial neural networks into spiking networks is scalable and works with a wide range of neural nonlinearities. We ac...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Neuroscience
سال: 2013
ISSN: 1471-2202
DOI: 10.1186/1471-2202-14-s1-p290