Open AccessNonlinear noise reduction for electrocorticograms
Author(s) -
Yong Xie,
Jianxue Xu,
Yanmei Kang,
Hongjun Yang,
HU San-jue
Publication year - 2003
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.52.1121
Subject(s) - reduction (mathematics) , noise (video) , noise reduction , gaussian noise , nonlinear system , white noise , additive white gaussian noise , value noise , gradient noise , control theory (sociology) , mathematics , computer science , physics , algorithm , noise measurement , acoustics , noise floor , statistics , artificial intelligence , quantum mechanics , geometry , control (management) , image (mathematics)
Local projective nonlinear noise reduction method,which is based on locally linear fits to the nonlinear dynamics,is introduced to reduce the noise in electrocorticograms of Spragure-Dawley rats.Recurrence plots are used to estimate the size of local neighbours.In this way,the noise reduction is improved markedly.In order to show that the program for noise reduction is correct,a noise reduction process is implemented for x-axial time series of Lorenz equation contaminated by 50% gaussian white noise.And then,this noise reduction scheme is applied separately to electrocorticograms of anaesthetized rats and those of the onset of epilepsy induced by penicillin in anaesthetized rats.The analyses of a nonlinear prediction demonstrate the efficiency of noise reduction.