| Abstract [eng] |
Since we encounter many phenomena with irregular motion, e.g. the weather, turbulence, carbon resistor noise, chemical reactions and biological signals (human motion), we are tempted to investigate whether we could model the dynamics with nonlinear differential equations. Our aim is to find order within the chaos; to find evidence that the irregular behavior is governed by a small set of deterministic equations, using experimental time series. We might be successful in particular when the state variables of the system are strongly coupled. In this report, we will restrict ourselves to the determination of several properties that describe a chaotic system, including the dimension and entropy spectra. Loosely speaking, the dimension is a measure for the number of differential equations needed to describe the system, while the entropy is a measure for the loss of information about the state of the system in the course of time. Positive but finite entropy is a hall-mark of chaos. In this paper, we will describe few experiments that were performed on a portion of human motion data, and compare the results to theoretical model of system for signal analysis. |
