Abstract:
In this paper we propose a novel and fast nonlinear association measure based on order statistics and rearrangement inequality. We employ one episode of heart signal, one...Show MoreMetadata
Abstract:
In this paper we propose a novel and fast nonlinear association measure based on order statistics and rearrangement inequality. We employ one episode of heart signal, one episode of EEG signal and 1000 white Gaussian noises in our study. Extensive statistical analysis are performed based on one linear model and one nonlinear model. Comparative studies with three other prominent methods are presented. Theoretical derivations and experimental results suggest that our new method has small biasedness, high sensitivity to changes in association, fast computational speed, and robustness under monotone nonlinear transformations.
Published in: 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings
Date of Conference: 14-19 May 2006
Date Added to IEEE Xplore: 24 July 2006
Print ISBN:1-4244-0469-X