Measuring information flow in nonlinear systems--a modeling approach in the state space
Document Type
Article
Abstract
Directional information flow between coupled nonlinear systems is of practical interest in many areas like bioengineering, chemistry, physics and electrical engineering. Due to the high complexity and nonlinearity of the coupled chaotic systems, linear modeling approaches may fail to capture the proper dynamics and thus the proper directional information flow. This necessitates novel approaches to analyze signals derived from such systems. This paper proposes a novel approach for detecting such directional information flows between the subsystems involved. The dependability of the method is illustrated using coupled chaotic oscillators in various coupling configurations.
Medical Subject Headings
Causality; Computer Simulation; Feedback; Models, Biological; Nonlinear Dynamics; Stochastic Processes; Systems Theory
Publication Date
1-1-2003
Publication Title
Biomedical sciences instrumentation
ISSN
0067-8856
Volume
39
First Page
65
Last Page
70
PubMed ID
12724870
Recommended Citation
Veeramani, Balaji; Prasad, Awadhesh; Narayanan, K; Spanias, A; and Iasemidis, L D., "Measuring information flow in nonlinear systems--a modeling approach in the state space" (2003). Translational Neuroscience. 1154.
https://scholar.barrowneuro.org/neurobiology/1154