Low-dimensional Chaotic Signal Characterization using Approximate Entropy

S. Ezekiel and M. Lang (USA)


Chaos, fractal dimension, approximate entropy,information dimension.


Many signals in physiology, geology, and market analysis look random and it has been assumed that the variations and fluctuations in such signals are due to a random process. However, these fluctuations may be chaotic or fractal in nature. In these cases, they would be a result of deterministic mechanisms. Therefore it is important to describe these signals in terms of their chaotic nature. This has tremendous significance in our understanding of these signals. In this paper, we present a method for characterizing low-dimensional chaotic signals. Our method uses a measure of approximate entropy of the attractor of a system as a basis for analysis. It is important to draw a distinction between systems that are noisy and those that truly exemplify chaotic behavior.

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