Decomposition of Multi-Valued Functions Into Min- And Max-Gates

This paper presents algorithms that allow the realization of multi-valued functions as a multi-level network consisting of min- and max-gates. The algorithms are based on bi-decomposition of function intervals, a generalization of incompletely specified functions. Multi-valued derivation operators are applied to compute decomposition structures. For validation the algorithms have been implemented in the YADE system. Results of the decomposition of functions from machine learning applications are listed and compared to the results of another decomposer