scholarly journals Fuzzy Interpolation Systems and Applications

Author(s):  
Longzhi Yang ◽  
Zheming Zuo ◽  
Fei Chao ◽  
Yanpeng Qu

Author(s):  
Jie Li ◽  
Hubert P. H. Shum ◽  
Xin Fu ◽  
Graham Sexton ◽  
Longzhi Yang


Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 170
Author(s):  
Michal Holčapek ◽  
Nicole Škorupová ◽  
Martin Štěpnička

The article develops further directions stemming from the arithmetic of extensional fuzzy numbers. It presents the existing knowledge of the relationship between the arithmetic and the proposed orderings of extensional fuzzy numbers—so-called S-orderings—and investigates distinct properties of such orderings. The desirable investigation of the S-orderings of extensional fuzzy numbers is directly used in the concept of S-function—a natural extension of the notion of a function that, in its arguments as well as results, uses extensional fuzzy numbers. One of the immediate subsequent applications is fuzzy interpolation. The article provides readers with the basic fuzzy interpolation method, investigation of its properties and an illustrative experimental example on real data. The goal of the paper is, however, much deeper than presenting a single fuzzy interpolation method. It determines direction to a wide variety of fuzzy interpolation as well as other analytical methods stemming from the concept of S-function and from the arithmetic of extensional fuzzy numbers in general.



Author(s):  
Haobin Shi ◽  
Xuesi Li ◽  
Huahui Chen ◽  
Shixiong Wang




2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Yonghui Sun ◽  
Zhinong Wei ◽  
Guoqiang Sun

This paper is concerned with positive stability analysis and bio-circuits design for nonlinear biochemical networks. A fuzzy interpolation approach is employed to approximate nonlinear biochemical networks. Based on the Lyapunov stability theory, sufficient conditions are developed to guarantee the equilibrium points of nonlinear biochemical networks to be positive and asymptotically stable. In addition, a constrained bio-circuits design with positive control input is also considered. It is shown that the conditions can be formulated as a solution to a convex optimization problem, which can be easily facilitated by using the Matlab LMI control toolbox. Finally, a real biochemical network model is provided to illustrate the effectiveness and validity of the obtained results.



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