Abstract
The models presented capture the intuition of the elementary differential calculus and provide the theoretical substrate for studying designs, schemas, shapes and constructions.
Unconventional frames for time and space, as for instance Galois fields or cyclic groups, have been used to describe the finite or cyclic type of separation and classification processes.
A wave equation is proposed as a differential model for separation and pattern recognition. This model is an abstract complement of transfer equations. The model generates design of experiment matrices as solutions.
Differential posets are introduced as powerful tools in the study of high complexity.
The connection with dual algebras is emphasized.
The notion of a differential category provides a basic axiomatization of differential operators for categories.
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Iordache, O. (2012). Differential Models. In: Self-Evolvable Systems. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28882-1_3
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DOI: https://doi.org/10.1007/978-3-642-28882-1_3
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