Institute of Mathematics AS CR, v. v. i.
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Properties of quantum logic maps as fuzzy relations on a set of all symmetric and idempotent binary matrices
Get PDFsummary:A quantum logic is one of possible mathematical models for non-compatible random events. In this work we solve a problem proposed at the conference FSTA 2006. Namely, it is proved that s-maps are symmetric fuzzy relations on a set of all symmetric and idempotent binary matrices. Consequently s-maps are not antisymmetric fuzzy relations. This paper also explores other properties of s-maps, j-maps and d-maps. Specifically, it is proved that s-maps are neither reflexive, nor irreflexive, and nor transitive, j-maps have the same properties as s-maps and d-maps are reflexive and not transitive
On the set function
No full textsummary:Inspired by the work that Professor Janusz R. Prajs did on homogeneous metric continua in his paper (2010) and the version of his work for Hausdorff continua with the uniform property of Effros done by this author, we introduce a new set function, , and present properties of it
Performance of parallel QR factorization methods on the NVIDIA Grace CPU Superchip
No full textsummary:This article studies several algorithms for QR factorization based on hierarchical Householder reflectors organized into elimination trees, which are particularly suited for tall-and-skinny matrices and allow parallelization. We examine the effect of various parameters on the performance of the tree-based algorithms. The work is accompanied with a custom implementation that utilizes a task-based runtime system (OpenMP or StarPU). The same algorithm is implemented in the PLASMA library. The performance evaluation is done on the recent NVIDIA Grace CPU Superchip
New hybrid conjugate gradient method for nonlinear optimization with application to image restoration problems
Get PDFsummary:The conjugate gradient method is one of the most effective algorithm for unconstrained nonlinear optimization problems. This is due to the fact that it does not need a lot of storage memory and its simple structure properties, which motivate us to propose a new hybrid conjugate gradient method through a convex combination of and . We compute the convex parameter using the Newton direction. Global convergence is established through the strong Wolfe conditions. Numerical experiments show the superior efficiency of our algorithm to solve unconstrained optimization problem compared to other considered methods. Applied to image restoration problem, our algorithm is competitive with existing algorithms and performs even better when the level of noise in the image is significant