Simulation of characteristics and artificial neural network modeling of electroencephalograph time series

被引：9

作者：

Kulkami, DR ^{[1
]}

Parikh, JC ^{[1
]}

Pratap, R ^{[1
]}

机构：

[1] COCHIN UNIV SCI & TECHNOL,DEPT PHYS,COCHIN 682022,KERALA,INDIA

来源：

PHYSICAL REVIEW E | 1997年 / 55卷 / 04期

关键词：

D O I：

10.1103/PhysRevE.55.4508

中图分类号：

O35 [流体力学]; O53 [等离子体物理学];

学科分类号：

070204 ; 080103 ; 080704 ;

摘要：

Electroencephalograph data of normal individuals viith their eyes closed is analyzed and modeled. The characteristics of the observed time series correspond to a filtered Gaussian random noise model modified with a suitable falloff in the power spectrum. An artificial neural, network model produces an excellent fit to the relatively short time series data without any hidden neurons, implying that the underlying system is predominantly deterministic and linear.

引用

页码：4508 / 4511

页数：4

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