Open AccessApplication of binary dynamical systems in the problem of classification of Boolean vectors
Author(s) -
Gennady A. Oparin,
Vera Bogdanova,
Anton A. Pashinin
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.47350/aicts.2020.15
Subject(s) - binary number , logical matrix , computer science , matrix (chemical analysis) , support vector machine , boolean function , simple (philosophy) , feature (linguistics) , feature vector , boolean data type , nonlinear system , standard boolean model , theoretical computer science , artificial intelligence , algorithm , and inverter graph , boolean expression , mathematics , philosophy , materials science , linguistics , chemistry , arithmetic , composite material , epistemology , quantum mechanics , physics , organic chemistry , group (periodic table)
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.