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oaioai:idus.us.es:11441/99045

Hardware Implementation of Convolutional STDP for On-line Visual Feature Learning

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Publication date
1 January 2017
Publisher
IEEE. Institute of Electrical and Electronics Engineers

Abstract

We present a highly hardware friendly STDP (Spike Timing Dependent Plasticity) learning rule for training Spiking Convolutional Cores in Unsupervised mode and training Fully Connected Classifiers in Supervised Mode. Examples are given for a 2-layer Spiking Neural System which learns in real time features from visual scenes obtained with spiking DVS (Dynamic Vision Sensor) Cameras.EU H2020 grant 644096 “ECOMODE”EU H2020 grant 687299 “NEURAM3”Ministry of Economy and Competitivity (Spain) /European Regional Development Fund TEC2012-37868-C04-01 (BIOSENSE)Junta de Andalucía (España) TIC-6091 (NANONEURO

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idUS. Depósito de Investigación Universidad de Sevilla

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Last time updated on 16/09/2020

This paper was published in idUS. Depósito de Investigación Universidad de Sevilla.

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