in this paper the 3d inversion of gravity data using two different regularization methods, namely tikhonov regularization and truncated singular value decomposition (tsvd), is considered. the earth under the survey area is modeled using a large number of rectangular prisms, in which the size of the prisms are kept fixed during the inversion and the values of densities of the prisms are the mode...

‎In this paper‎, ‎we consider an inverse boundary value problem for two-dimensional heat equation in an annular domain‎. ‎This problem consists of determining the temperature on the interior boundary curve from the Cauchy data (boundary temperature and heat flux) on the exterior boundary curve‎. ‎To this end‎, ‎the boundary integral equation method is used‎. ‎Since the resulting system of linea...

This work deals with the problem of identification of Discrete Possibilistic Dynamic System (DPDS), using the technologies of Genetic Algorithmms (GA). Applying the results from [5-9,11-13,15,16,18-20], the fuzzy recurrent process with possibilistic uncertainty, the source of which is expert knowledge reflections on the states of evolutionary complex extremal system, is constructed. The dynamic...

We develop an analytical approach to scalar field theory on the fuzzy sphere based on considering a perturbative expansion of the kinetic term. This expansion allows us to integrate out the angular degrees of freedom in the hermitian matrices encoding the scalar field. The remaining model depends only on the eigenvalues of the matrices and corresponds to a multitrace hermitian matrix model. Suc...

We offer an efficient method to reduce the number of support vectors for Fuzzy Support Vector Machine. Firstly, we consider the Fuzzy Support Vector Machine model which was proposed by Lin and Wang. For the reducing the number of support vectors, we apply the l0 regularization term to the dual form of this model. The resulting optimization problem is non-smooth and non-convex. The l0 is then re...

It is considered t the Takagi-Sugeno-Kang fuzzy neural network and its modern variations. The use of regularization, random exclusion rules from rule base allows solving problem excessive similarity in base. batch normalization to increase generalizing properties accuracy model, while maintaining possibility interpreting results, which characteristic networks. proposed an ensemble networks capa...

Color image segmentation is a fundamental task in many computer vision problems. A common approach is to use fuzzy iterative clustering algorithms that provide a partition of the pixels into a given number of clusters. However, most of these algorithms present several drawbacks: they are time consuming, and sensitive to initialization and noise. In this paper, we propose a new fuzzy c-means alg...

This paper explains the approximation of a membership function obtained by entropy regularization of the fuzzy c-means (FCM) method. By regularizing FCM with fuzzy entropy, a membership function similar to the Fermi-Dirac distribution function is obtained. We propose a new clustering method, in which the minimum of the Helmholtz free energy for FCM is searched by deterministic annealing (DA), w...

Ćurić, V. 2014. Distance Functions and Their Use in Adaptive Mathematical Morphology. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1137. 88 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-8923-6. One of the main problems in image analysis is a comparison of different shapes in images. It is often desirable to determine the exte...