It is constructively proved that the multi-input–multi-output fuzzy systems based upon genuine many-valued implications are universal approximators (they are called Boolean type fuzzy systems in this paper). The general approach to construct such fuzzy systems is given, that is, through the partition of the output region (by the given accuracy). Two examples are provided to demonstrate the way ...

We present graded extension of the algorithm LinClosure. Graded LinClosure can be used to compute degrees of semantic entailment from sets of fuzzy attribute implications. It can also be used together with graded extension of Ganter’s NextClosure algorithm to compute non-redundant bases of data tables with fuzzy attributes. We present foundations, algorithm, preliminary analysis of its complexi...

We present and analyze inference method called Perception-based Logical Deduction (PbLD) aimed at the treatment of fuzzy IF-THEN rules as linguistically expressed genuine logical implications. Besides the original PbLD, we propose a new balancing variant of PbLD, introduce both variants with fuzzy inputs and study them from the point of view of the interpolativity property.

We present graded extension of the algorithm LinClosure. Graded LinClosure can be used to compute degrees of semantic entailment from sets of fuzzy attribute implications. It can also be used together with graded extension of Ganter’s NextClosure algorithm to compute non-redundant bases of data tables with fuzzy attributes. We present foundations, the algorithm, and illustrative examples.

Recently, the distributivity of fuzzy implications over t-norms, t-conorms and uninorms was studied in many articles. In this paper we characterize functions which satisfy one of the four generalized distributivity equations of classical implication in the case when t-conorms are continuous and Archimedean. Using the obtained characterizations we describe some solutions which are fuzzy implicat...

This paper shows, by examples, that Lemma 2.1, Lemma 3.1, Corollary 3.1, Corollary 3.2, Theorem 3.1, Corollary 3.3, Theorem 3.3 and Lemma 4.1 in [Y. Luo, Resolution of fuzzy relation equation (I) based on Boolean-type implications, Comput. Math. Appl. 52 (2006) 421–428] about resolution of fuzzy relation equations based on Boolean-type implications, are false. We also point out that the solutio...

A sequentiality study for mixed-signal VLSI implementations of neuro/fuzzy feedforward algorithms is presented. Implications of sequential processing and mixed-signal operation are derived. Basic building blocks for sequential mixed-signal neural and fuzzy computing are proposed, and two sequential example processors are described. Feedback from designed processors and subcircuits allows consid...

In this paper, a model for fuzzy risk of low yield of a crop is developed to study the implications of a reservoir operating policy model. When an optimal operating policy is derived based on a known objective, the policy itself does not, in general, indicate a measure of the system performance unless a criterion to this effect is embedded in the objective function. While a systems analyst is i...

Modus Ponens is a key property for fuzzy implication functions that are going to be used in fuzzy inference processes. In this paper it is investigated when fuzzy implication functions derived from uninorms via residuation, usually called RU implications, satisfy the modus ponens with respect to a continuous t-norm T , or equivalently, when they are T -conditionals. For RU -implications it is p...