نتایج جستجو برای: fuzzy eigenvalue

تعداد نتایج: 107456  

Journal: :Journal of Physics A: Mathematical and Theoretical 2020

Journal: :Soft Computing 2023

In this paper, we propose a new method to obtain the eigenvalues and fuzzy triangular eigenvectors of matrix $$\left( {\tilde{A}} \right)$$ , where elements are given. For purpose, solve 1-cut eigenvectors. Considering interval system $$\left[ \right]_{\alpha } \left[ {\tilde{X}} = {\tilde{\lambda }} 0 \le \alpha 1$$ as α-cut $$\tilde{A}\tilde{X} \tilde{\lambda }\tilde{X}$$ determine left right...

2014
P. - W. Tsai C. - Y. Chen C. - W. Chen

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking perf...

Journal: :Inf. Sci. 2013
Heinrich Fritz Luis Angel García-Escudero Agustín Mayo-Iscar

It is well-known that outliers and noisy data can be very harmful when applying clustering methods. Several fuzzy clustering methods which are able to handle the presence of noise have been proposed. In this work, we propose a robust clustering approach called F-TCLUST based on an “impartial” (i.e., self-determined by data) trimming. The proposed approach considers an eigenvalue ratio constrain...

2011
Chung-Shi Tseng Yung-Yue Chen

This study introduces decentralized static output feedback fuzzy control design for nonlinear interconnected systems via T-S fuzzy models. In general, due to the interactions among subsystems, it is dif cult to design an decentralized output feedback controller for nonlinear interconnected systems. A singular value decomposition (SVD) method is proposed in this study to solve the decentralized ...

Journal: :Inf. Sci. 2013
Mario Rosario Guarracino Antonio Irpino Raimundas Jasinevicius Rosanna Verde

Supervised classification of data affected by noise or error, with unknown probability distribution, is a challenging task. To this extend, we propose the Fuzzy Regularized Eigenvalue Classifier, based on a recent technique to classify data in two or more classes. We compare the execution time and accuracy of the classifier with other de facto standard methods. With the adoption of a novel memb...

Journal: :Appl. Soft Comput. 2004
Lanka Udawatta Keigo Watanabe Kazuo Kiguchi Kiyotaka Izumi

A novel approach for solving fuzzy model-based stability problems via evolutionary computation (EC) is presented. Gain scheduling problem of a multi-model fuzzy system that satisfies the Lyapunov stability criteria is solved. The generalized eigenvalue problem (GEVP) can be directly introduced to EC in searching positive definite (PD) or positive semi-definite (PSD) matrices, by making a penalt...

Journal: :Turkish Journal of Electrical Engineering and Computer Sciences 2022

Recently, a precise and stable machine learning algorithm, i.e. eigenvalue classification method (EigenClass), has been developed by using the concept of generalised eigenvalues in contrast to common approaches, such as k-nearest neighbours, support vector machines, decision trees. In this paper, we offer new algorithm called fuzzy parameterized soft aggregation classifier (FPFS-AC) combine mod...

Among the eigenvalue problems of the Laplacian, the biharmonic operator eigenvalue problems are interesting projects because these problems root in physics and geometric analysis. The buckling problem is one of the most important problems in physics, and many studies have been done by the researchers about the solution and the estimate of its eigenvalue. In this paper, first, we obtain the evol...

Journal: :Applied Mathematics and Computation 2006
Ying-Ming Wang Kwai-Sang Chin

Crisp comparison matrices produce crisp weight estimates. It is logical for an interval or fuzzy comparison matrix to give an interval or fuzzy weight estimate. In this paper, an eigenvector method (EM) is proposed to generate interval or fuzzy weight estimate from an interval or fuzzy comparison matrix, which differs from Csutora and Buckley’s LambdaMax method in several aspects. First, the pr...

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