Lyapunov exponent and natural invariant density determination of chaotic maps: An iterative maximum entropy ansatz

Nonlinear Sciences – Chaotic Dynamics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

16 pages including 6 figures

Scientific paper

We apply the maximum entropy principle to construct the natural invariant density and Lyapunov exponent of one-dimensional chaotic maps. Using a novel function reconstruction technique that is based on the solution of Hausdorff moment problem via maximizing Shannon entropy, we estimate the invariant density and the Lyapunov exponent of nonlinear maps in one-dimension from a knowledge of finite number of moments. The accuracy and the stability of the algorithm are illustrated by comparing our results to a number of nonlinear maps for which the exact analytical results are available. Furthermore, we also consider a very complex example for which no exact analytical result for invariant density is available. A comparison of our results to those available in the literature is also discussed.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Lyapunov exponent and natural invariant density determination of chaotic maps: An iterative maximum entropy ansatz 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 Lyapunov exponent and natural invariant density determination of chaotic maps: An iterative maximum entropy ansatz, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Lyapunov exponent and natural invariant density determination of chaotic maps: An iterative maximum entropy ansatz will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-424099

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.