The theory of fuzzy/blurry models is an alternative approach to the formalization of uncertainty and incompleteness of knowledge with respect to formalization by means of fuzzy sets proposed by Lotfi Zadeh. The fundamental distinctive feature of the mathematical foundations of this approach is that initially one deals with a set of precedents in which certain events occur, rather than with the numerical estimates of the probability that these events occur in a given object field. Within the approach proposed, all available information is first completely processed, and only the final result is fuzzified and converted into numbers in the interval 0, 1. This approach to information processing is also used in quantum computing. One of the main differences of quantum computing from the classical one is that before starting calculations we know only the probabilistic (fuzzy) values of qubit states. Thus, all quantum computations are performed under conditions of incomplete knowledge, and the measurement (i.e., digitization) of the results is performed only at the final stage. The paper presents a semantic interpretation of finite fuzzy models as a generalization of quantum systems. The concepts of a separable system and a totally entangled system are considered and generalized to the fuzzy case. Existence and uniqueness theorems of such systems are proved.
Gulnara Erkinovna Yakhyaeva (2025) studied this question.