Relative performance of mutual information estimation methods for quantifying the dependence among short and noisy data-Reference-Cited by-同舟云学术

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Relative performance of mutual information estimation methods for quantifying the dependence among short and noisy data

Published:2007-08-14 Issue:2 Volume:76 Page:
ISSN:1539-3755
Container-title:Physical Review E
language:en
Short-container-title:Phys. Rev. E

Author:

Khan Shiraj,Bandyopadhyay Sharba,Ganguly Auroop R.,Saigal Sunil,Erickson David J.,Protopopescu Vladimir,Ostrouchov George

Publisher

American Physical Society (APS)

Subject

Industrial and Manufacturing Engineering,Metals and Alloys,Strategy and Management,Mechanical Engineering

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevE.76.026209/fulltext

Reference30 articles.

1. Detection of nonlinear dynamics in short, noisy time series

2. Detection and predictive modeling of chaos in finite hydrological time series

3. Re-examination of the evidence for low-dimensional, nonlinear structure in the human electroencephalogram

4. Can Epileptic Seizures be Predicted? Evidence from Nonlinear Time Series Analysis of Brain Electrical Activity

5. Estimation of interaction strength and direction from short and noisy time series

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