DocumentCode
3498218
Title
Local learning rules for spiking neurons with dendrite
Author
Manette, Olivier F L
Author_Institution
Centre Nat. de Rech. Scientifiques, UNIC, Gif-sur-Yvette, France
fYear
2011
fDate
July 31 2011-Aug. 5 2011
Firstpage
2217
Lastpage
2221
Abstract
We present in this article four local rules to train a network of spiking dendritic neurons. After training, every neuron of the network becomes specialized for a particular feature of the input signal. With these rules, the network acts as a features extractor where each neuron contains a TAND vector, similar to logical AND but including information about time between the two events in the input signal.
Keywords
learning (artificial intelligence); neural nets; TAND vector; features extractor; local learning rules; logical AND; network training; spiking dendritic neurons; spiking neurons; Biological system modeling; Feature extraction; Firing; Mathematical model; Neurons; Radio frequency;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location
San Jose, CA
ISSN
2161-4393
Print_ISBN
978-1-4244-9635-8
Type
conf
DOI
10.1109/IJCNN.2011.6033504
Filename
6033504
Link To Document