Browsing by Subject "Fuzzy sets"

Now showing 1 - 4 of 4

Open Access
Computation of the resonant frequency of electrically thin and thick rectangular microstrip antennas with the use of fuzzy inference systems
(John Wiley & Sons, 2000) Özer, Ş.; Güney, K.; Kaplan, A.
A new method for calculating the resonant frequency of electrically thin and thick rectangular microstrip antennas, based on the fuzzy inference systems, is presented. The optimum design parameters of the fuzzy inference systems are determined by using the classical, modified, and improved tabu search algorithms. The calculated resonant frequency results are in very good agreement with the experimental results reported elsewhere.
Open Access
Concave measures and the fuzzy core of exchange economies with heterogeneous divisible commodities
(Elsevier BV, 2012) Hüsseinov, F.; Sagara, N.
The main purpose of this paper is to prove the existence of the fuzzy core of an exchange economy with a heterogeneous divisible commodity in which preferences of individuals are given by nonadditive utility functions defined on a σ-algebra of admissible pieces of the total endowment of the commodity. The problem is formulated as the partitioning of a measurable space among finitely many individuals. Applying the Yosida-Hewitt decomposition theorem, we also demonstrate that partitions in the fuzzy core are supportable by prices in L 1. © 2012 Elsevier B.V.
Open Access
Fuzzy clustering and enumeration of target type based on sonar returns
(Elsevier, 2004) Barshan, B.; Ayrulu, B.
The fuzzy c-means (FCM) clustering algorithm is used in conjunction with a cluster validity criterion, to determine the number of different types of targets in a given environment, based on their sonar signatures. The class of each target and its location are also determined. The method is experimentally verified using real sonar returns from targets in indoor environments. A correct differentiation rate of 98% is achieved with average absolute valued localization errors of 0.5 cm and 0.8° in range and azimuth, respectively.
Open Access
Relative position-based spatial relationships using mathematical morphology
(IEEE, 2007-09-10) Cinbiş, R. Gökberk; Aksoy, Selim
Spatial information is a crucial aspect of image understanding for modeling context as well as resolving the uncertainties caused by the ambiguities in low-level features. We describe intuitive, flexible and efficient methods for modeling pairwise directional spatial relationships and the ternary between relation using fuzzy mathematical morphology. First, a fuzzy landscape is constructed where each point is assigned a value that quantifies its relative position according to the reference object(s) and the type of the relationship. Then, the degree of satisfaction of this relation by a target object is computed by integrating the corresponding landscape over the support of the target region. Our models support sensitivity to visibility to handle areas that are partially enclosed by objects and are not visible from image points along the direction of interest. They can also cope with the cases where one object is significantly spatially extended relative to others. Experiments using synthetic and real images show that our models produce more intuitive results than other techniques. ©2007 IEEE.