ABSTRACT
In this chapter, the authors examine a different aspect of a nonlinear system: the information carried in its signals. They start the discussion of information analysis of signals by first describing what the people mean by information and entropy. One way to estimate the rate at which entropy is lost, as well as to get a sense of how the system properties change at differing scales, is to use the mutual information function. Spectral entropy’s strength, and weakness, is that it is based on the power spectrum of the signal. The topics presented here provide a good starting point for entropy-based analyses of signals. DFA is not an entropy-based method, but it shares with MSE the feature of describing how a signal changes as a function of scale. For a more detailed discussion of the methods described here, the reader is encouraged to refer to the references in the Bibliography.
