.png){kind=icon}
.png){kind=icon}
Return
Nonlinear model for ECG R-R interval variation using genetic programming approach
.png){kind=icon}
PRE
AI
DOI：10.1016/j.future.2004.03.011.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper proposes a nonlinear system modeling method, which predicts characteristics of the ECG R-R interval variation. For determining model equation, we adopted a genetic programming method in which the chromosome represents the model equation consisting of time-delayed variables, constants, and four arithmetic operators, and determines the fitness function. By genetic programming, sequences of regressive nonlinear equations are produced and evolved until the finding of the optimal model equation, which could simulate the spectral, statistical and nonlinear behavior of the given R-R interval dynamics. Experimental results showed that the evolutionary approach could find the equation which simulates the spectral and chaotic dynamics of the given signal. Therefore, the proposed evolutionary approach is useful for the system identification of the nonlinear biological system. (c) 2004 Published by Elsevier B.V.
Keywords:
genetic programming
modeling nonlinear system
nonlinear equation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
F
IF:
6.1
Papers:
6.8K
Citations:
2.3W
Organization
No organization information available