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Título: | Hardware implementation of convolutional STDP for on-line visual feature learning |
Autor: | Yousefzadeh, Amirreza CSIC ORCID; Masquelier, T.; Serrano-Gotarredona, Teresa CSIC ORCID ; Linares-Barranco, Bernabé CSIC ORCID | Palabras clave: | Spike Time Dependent Plasticity (STDP) Spiking Neural Networks Hardware Implementation of Neural Systems Neuromorphic systems Learning Systems |
Fecha de publicación: | 2017 | Editor: | Institute of Electrical and Electronics Engineers | Citación: | IEEE International Symposium on Circuits and Systems (2017) | Resumen: | 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. | Descripción: | Paper presented at the 2017 IEEE International Symposium on Circuits and Systems (ISCAS), held in Baltimore, MD, USA, on 28-31 May 2017. | Versión del editor: | https://doi.org/10.1109/ISCAS.2017.8050870 | URI: | http://hdl.handle.net/10261/195582 | DOI: | 10.1109/ISCAS.2017.8050870 | ISBN: | 978-1-5090-1427-9 | E-ISSN: | 2379-447X |
Aparece en las colecciones: | (IMSE-CNM) Libros y partes de libros |
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