Evolving spiking neural networks for spatio-and spectro-temporal pattern recognition

Author

Kasabov, Nikola

Author_Institution

Knowledge Eng. & Discovery Res. Inst. - KEDRI, Auckland Univ. of Technol., Auckland, New Zealand

fYear

2012

fDate

6-8 Sept. 2012

Firstpage

27

Lastpage

32

Abstract

This paper provides a survey on the evolution of the evolving connectionist systems (ECOS) paradigm, from simple ECOS introduced in 1998 to evolving spiking neural networks (eSNN) and neurogenetic systems. It presents methods for their use for spatio-and spectro temporal pattern recognition. Future directions are highlighted.

Keywords

genetics; neural net architecture; neurophysiology; pattern recognition; spatiotemporal phenomena; ECOS paradigm; eSNN; evolving connectionist systems paradigm; evolving spiking neural networks; neurogenetic systems; spatio-temporal pattern recognition; spectro-temporal pattern recognition; Adaptation models; Biological system modeling; Brain models; Computational modeling; Data models; Neurons; Computational Neurogenetic Systems (CNGS); Evolving Connectionist Systems (ECOS); Evolving Spiking Neural Networks (eSNN); quantum inspired SNN; spatio-temporal pattern recognition; spectro-temporal pattern recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems (IS), 2012 6th IEEE International Conference

Conference_Location

Sofia

Print_ISBN

978-1-4673-2276-8

Type

conf

DOI

10.1109/IS.2012.6335110

Filename

6335110