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Journal of Automation and Information Sciences
SJR: 0.238 SNIP: 0.464 CiteScore™: 0.27

ISSN Imprimir: 1064-2315
ISSN En Línea: 2163-9337

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

Journal of Automation and Information Sciences

DOI: 10.1615/J Automat Inf Scien.v37.i2.60
pages 46-54

Algorithms of Classification of Neuron Impulses Based on Dynamic Equations

Olga K. Chibirova
Joseph Fourier University, Grenoble, France
Steve Larouche
Sherbrooke University, Canada
Alesandro E. P. Villa
Joseph Fourier University, Grenoble, France
Tatyana I. Aksenova
Zhozef Fourier University, Grenoble, France

SINOPSIS

A description of computer implementation of an algorithm for classification of neuron impulses (ACNI) using nonlinear dynamic equations is given. ACNI includes an automated learning procedure and allows a real-time classification of impulses of several neurons, recorded by a single microelectrode. Results of algorithm testing on a simulated signal with different noise levels are presented. We also demonstrate applications of ACNI for studying of neuron activity in the subthalamic kernel of brain, which is the goal zone for high-frequency electric stimulation of depth zones of brain in Parkinson's disease.


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