Application of binary dynamical systems in the problem of classification of Boolean vectors

The article proposes a method based on using binary dynamical systems in the classification problem for Boolean vectors (binary feature vectors). This problem has practical application in various fields of science and industry, for example, bioinformatics, remote sensing of natural objects, smart devices of the Internet of things, etc. Binary synchronous autonomous nonlinear dynamic models with an unknown characteristic matrix are considered. Matrix elements are chosen in such a way that the Boolean reference vectors are equilibrium states of the binary dynamic model. The attraction regions of equilibrium states act as classes (one reference vector corresponds to each class). The classified vector is the initial state of the model. Simple and aggregated classifiers are considered. The proposed method is demonstrated using an illustrative example.