Evolving Systems

, Volume 4, Issue 2, pp 87–98 | Cite as

Evolving spiking neural network—a survey

  • Stefan Schliebs
  • Nikola Kasabov
Original Paper


This paper provides a comprehensive literature survey on the evolving Spiking Neural Network (eSNN) architecture since its introduction in 2006 as a further extension of the ECoS paradigm introduced by Kasabov in 1998. We summarize the functioning of the method, discuss several of its extensions and present a number of applications in which the eSNN method was employed. We focus especially on some proposed extensions that allow the processing of spatio-temporal data and for feature and parameter optimisation of eSNN models to achieve better accuracy on classification/prediction problems and to facilitate new knowledge discovery. Finally, some open problems are discussed and future directions highlighted.


Evolving Spiking Neural Network Evolving Connectionist Systems spatio-temporal pattern recognition 


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.KEDRIAuckland University of TechnologyAucklandNew Zealand
  2. 2.Institute for Neuroinformatics, ETH/UZHZurichSwitzerland

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