Features Samples Cardiointervals: Chaos and Stochastics in the Description of Complex Biosystems

Abstract

Complex Biosystems (complexity) cannot be attributed to traditional chaotic systems, because for them it is impossible to calculate the autocorrelation function, Lyapunov exponent, no run properties of mixing, continuously the state vector x(t) demonstrates chaotic motion in the form άχίάίΦθ. Since the initial state x(to) is arbitrarily unrepeatable for such systems, type-one uncertainty and type-two uncertainty arise. Type-one uncertainty is characterized by absence of statistically significant differences between samples. The authors propose neurocomputing methods and theory of chaos and self-organization to differentiate these samples. The authors present examples of such a situation for the parameters of the cardio-respiratory system of humans in conditions of the latitudinal displacement of large groups of people. It is shown that the neuroemulator not only solves the problem of binary classification, but also identifies the order parameters in diagnostic signs. It is very important to increase the number of iterations in the repetition of binary classification. The number of iteration (when we repeat the neuroemulator procedure) has the fundamental role for identification of order parameters. Errors are possible within the order parameters with the high number of iterations.