Methods in Complexity Analysis of Discrete Time Signals

Discrete time signals carry information about systems and their internal functional mechanisms which characterize their complexity. Complexity measures are strongly related to information content and evaluations have been made on various signals in many ways in last few years. This paper uses information theory estimates of complexity as different types of entropies in order to estimate the complexity of various time discrete synthesized signals. Results show that this kind of indices can be a useful tool in diagnostic, fault detection and further development.