Calculating the entropy for complex systems is a significant problem in science and engineering problems. However, this calculation is usually computationally expensive when the entropy is computed directly. This paper introduces three classes of information sources that for all members of each class, the entropy value is the same. These classes are characterized according to special dynamics created by three kinds of self-mappings on Ω, and , where Ω is a probability space and is a finite set. An approximation of rank variables of the product of information sources is made, and it is proved that the topological entropy of the product of two information sources is equal to the summation of their topological entropies.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631386 | PMC |
| http://dx.doi.org/10.1080/02664763.2022.2101631 | DOI Listing |
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