Noise level estimation of time series using coarse grained entropy

Details Noise level estimation of time series using coarse grained entropy Noise level estimation of time series using coarse grained entropy

2003-01-17

arxiv.org/abs/cond-mat/0301326v3

Phys. Rev. E 67, 046218, (2003)

Physics

Condensed Matter

Statistical Mechanics

14 pages, 4 figures. See http://www.chaosandnoise.org

Scientific paper

10.1103/PhysRevE.67.046218

We present a method of noise level estimation that is valid even for high noise levels. The method makes use of the functional dependence of coarse grained correlation entropy $K_2(\eps)$ on the threshold parameter $\eps$. We show that the function $K_2(\eps)$ depends in a characteristic way on the noise standard deviation $\sigma$. It follows that observing $K_2(\eps)$ one can estimate the noise level $\sigma$. Although the theory has been developed for the gaussian noise added to the observed variable we have checked numerically that the method is also valid for the uniform noise distribution and for the case of Langevine equation corresponding to the dynamical noise. We have verified the validity of our method by applying it to estimate the noise level in several chaotic systems and in the Chua electronic circuit contaminated by noise.

Affiliated with

Also associated with

No associations

Rating

Noise level estimation of time series using coarse grained entropy does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Noise level estimation of time series using coarse grained entropy, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Noise level estimation of time series using coarse grained entropy will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-646509