Syntropy in complex systems: A complement to Shannon's Entropy
Abstract
This study introduces the syntropy function ($S_N$) and expectancy function ($E_N$), derived from the novel function $\phi$, to provide a refined perspective on complexity, extending beyond conventional entropy analysis. $S_N$ is designed to detect localized coherent events, whereas $E_N$ encapsulates expected system behaviors, offering a comprehensive framework for understanding system dynamics. The manuscript explores essential theorems and properties, underscoring their theoretical and practical implications. Future research will further elucidate their roles, particularly in biological signals and dynamic systems, suggesting a deep interplay between order and chaos.
- Publication:
-
arXiv e-prints
- Pub Date:
- March 2024
- DOI:
- 10.48550/arXiv.2403.13022
- arXiv:
- arXiv:2403.13022
- Bibcode:
- 2024arXiv240313022M
- Keywords:
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- Condensed Matter - Statistical Mechanics;
- Computer Science - Information Theory;
- Mathematical Physics;
- Mathematics - Dynamical Systems;
- 94A17;
- G.3
- E-Print:
- 26 pages, 13 figures