Title
SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.
Abstract
This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perfor...
Year
DOI
Venue
2017
10.1109/TNNLS.2015.2501322
IEEE Transactions on Neural Networks and Learning Systems
Keywords
Field
DocType
Neurons,Encoding,Learning systems,Training,Sociology,Statistics,Adaptive systems
Population,ENCODE,Data set,Pattern recognition,Random neural network,Adaptive system,Computer science,Gaussian,Artificial intelligence,Spiking neural network,Machine learning,Encoding (memory)
Journal
Volume
Issue
ISSN
28
1
2162-237X
Citations 
PageRank 
References 
14
0.60
23
Authors
4
Name
Order
Citations
PageRank
Jinling Wang1452.59
A. Belatreche216512.40
liam maguire3352.82
Thomas Martin McGinnity4181.09