We propose novel metrics based on the Kolmogorov complexity for use in complex system behavior studies and time series analysis. We consider the origins of the Kolmogorov complexity and discuss its physical meaning. To get better insights into the nature of complex systems and time series analysis we introduce three novel measures based on the Kolmogorov complexity: (i) the Kolmogorov complexity spectrum, (ii) the Kolmogorov complexity spectrum highest value and (iii) the overall Kolmogorov complexity. The characteristics of these measures have been tested using a generalized logistic equation. Finally, the proposed measures have been applied to different time series originating from: a model output (the biochemical substance exchange in a multi-cell system), four different geophysical phenomena (dynamics of: river flow, long term precipitation, indoor 222Rn concentration and UV radiation dose) and the economy (stock price dynamics). The results obtained offer deeper insights into the complexity of system dynamics and time series analysis with the proposed complexity measures.
 V. Arshinov, C. Fuchs, Causality, Emergence, Self-Organisation, (NIA-Priroda, Moscow, 2003)
 B. Edmonds, What is Complexity? - The Philosophy of Complexity per se with Application to Some Examples in Evolution, In: F. Heylighen, D. Aerts (Eds.) The Evolution of Complexity, (Dordrecht, Kluwer, 1999)
 S. Kauffman, The Origins of Order, (Oxford University Press, Oxford, 1993)
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.