Inscrição na biblioteca: Guest
Portal Digital Begell Biblioteca digital da Begell eBooks Diários Referências e Anais Coleções de pesquisa
Journal of Automation and Information Sciences
SJR: 0.232 SNIP: 0.464 CiteScore™: 0.27

ISSN Imprimir: 1064-2315
ISSN On-line: 2163-9337

Volumes:
Volume 51, 2019 Volume 50, 2018 Volume 49, 2017 Volume 48, 2016 Volume 47, 2015 Volume 46, 2014 Volume 45, 2013 Volume 44, 2012 Volume 43, 2011 Volume 42, 2010 Volume 41, 2009 Volume 40, 2008 Volume 39, 2007 Volume 38, 2006 Volume 37, 2005 Volume 36, 2004 Volume 35, 2003 Volume 34, 2002 Volume 33, 2001 Volume 32, 2000 Volume 31, 1999 Volume 30, 1998 Volume 29, 1997 Volume 28, 1996

Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v45.i3.30
pages 23-33

Self-Learning Cascade Spiking Neural Network for Fuzzy Clustering Based on Group Method of Data Handling

Yevgeniy .V. Bodyanskiy
Kharkov National University of Radioelectronics
Elena A. Vynokurova
Kharkov National University of Radioelectronics
Artem I. Dolotov
Kharkov National University of Radioelectronics

RESUMO

The fuzzy clustering problem in the presence of overlapping classes is considered. To solve the problem, it is introduced the architecture and learning algorithm of a fuzzy spiking neural network, generalizing neural networks of the third generation, which at present are developing intensively and have a number of advantages over traditional computational intelligence systems. The spiking neuron is described as a nonlinear dynamic system, which simplifies the hardware implementation. For problems with high dimension of input vectors-images it is proposed to use the hybrid architecture, which is based on a combination of cascade and GMDH-neural networks with self-learning cascade spiking neural networks, used as nodes, and ensures the increased speed of information processing.


Articles with similar content:

Determination of Optimal Routes of Single-Frame Shooting by Spacecrafts and Their Clusters
Journal of Automation and Information Sciences, Vol.47, 2015, issue 1
Vsevolod M. Kuntsevich
AN ENSEMBLE KALMAN FILTER USING THE CONJUGATE GRADIENT SAMPLER
International Journal for Uncertainty Quantification, Vol.3, 2013, issue 4
Heikki Haario, Antti Solonen, Albert Parker, Marylesa Howard, Johnathan M. Bardsley
Use of an Adaptive Neuron Network in the Voice Authentication System
Telecommunications and Radio Engineering, Vol.65, 2006, issue 1-5
V. A. Pimenov, A. P. Ryzhkov
Application of a Nonlinear Trade-off Scheme in the Problem of Structure Synthesis of the Data Transfer Systems
Journal of Automation and Information Sciences, Vol.35, 2003, issue 5
Sergey A. Shvorov, Maxim V Tkachenko, Pavel D. Mosorin
Hybrid Algorithm for Identification of Linear by States Hammerstein Model
Journal of Automation and Information Sciences, Vol.46, 2014, issue 1
Fedor G. Garashchenko, Olga G. Moroz