Algebraic methods for solving recognition problems with non-crossing classes
This work addresses pattern recognition problems, but appears incremental as it builds on existing operator-based models with algebraic extensions.
The paper tackles pattern recognition by modeling it with two operators and introducing algebraic operations on recognizing operators to create a family of algorithms, resulting in an upper estimate that guarantees completeness of extension.
In this paper, we propose to consider various models of pattern recognition. At the same time, it is proposed to consider models in the form of two operators: a recognizing operator and a decision rule. Algebraic operations are introduced on recognizing operators, and based on the application of these operators, a family of recognizing algorithms is created. An upper estimate is constructed for the model, which guarantees the completeness of the extension.