Topic
Fuzzy associative matrix
About: Fuzzy associative matrix is a research topic. Over the lifetime, 8027 publications have been published within this topic receiving 194790 citations.
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TL;DR: The author studies the Smarandache Fuzzy Algebra, which arose from the need to define structures that were more compatible with the real world where the grey areas mattered, not only black or white.
Abstract: The author studies the Smarandache Fuzzy Algebra, which, like its predecessor Fuzzy Algebra, arose from the need to define structures that were more compatible with the real world where the grey areas mattered, not only black or white.
This book has seven chapters, which are divided into two parts. Part I contains the first chapter, and Part II encloses the remaining six chapters. In the first chapter (which also forms the first part), which is subdivided into twelve sections, we deal with eleven distinct fuzzy algebraic concepts and in the concluding section list the miscellaneous properties of fuzzy algebra. The eleven fuzzy algebraic concepts which we analyze are fuzzy sets, fuzzy subgroups, fuzzy sub-bigroups, fuzzy rings, fuzzy birings, fuzzy fields, fuzzy semirings, fuzzy near-rings, fuzzy vector spaces, fuzzy semigroups and fuzzy half-groupoids. The results used in these sections are extensive and we have succeeded in presenting new concepts defined by several researchers.
84 citations
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TL;DR: Using fuzzy measures and fuzzy integrals, a mathematical model of learning is presented which is able to learn through fuzzy information and is compared with an ordinary Bayesian learning model.
Abstract: Using fuzzy measures and fuzzy integrals, the paper presents a mathematical model of learning which is able to learn through fuzzy information. The characteristics of the model are studied theoretically and in numerical examples, where the model is compared with an ordinary Bayesian learning model. The problem of seeking an extremum of multimodel objective function is given as an example.
84 citations
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TL;DR: Both delay-independent and delay-dependent results are presented, and the theoretical results are given in terms of linear matrix inequalities (LMIs).
Abstract: Takagi-Sugeno (T-S) fuzzy model provides an effective representation of complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear input/output submodels. Recently, a number of authors studied the T-S fuzzy systems with time delays. In this paper, the passivity and feedback passification of T-S fuzzy systems with time delays are considered. Both delay-independent and delay-dependent results are presented, and the theoretical results are given in terms of linear matrix inequalities (LMIs). Numerical examples are given which illustrate the effectiveness of the theoretical results.
84 citations
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84 citations
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TL;DR: A novel approach is presented to use the finite element analysis as a “numerical experiment” tool, and to find directly, by fuzzy linear regression method, the statistical property of the structure stress.
83 citations