Examples of using Matrices in English and their translations into Czech
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Colloquial
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Official
Linear mappings and their matrices.
Inverse matrices and their calculation.
Noncommutative geometry, random matrices.
These matrices are incompatible.
Schur triangularization theorem and normal matrices.
These matrices are incompatible with our emitters.
Hermitian, unitary andreal orthogonal matrices.
Operations with matrices and vectors, declarations, calculations.
Basic routines for numerical linear algebra dense matrices.
Landscape structure: matrices, patches, corridors, network allowance 2/0.
Eigenvalues and eigenvectors of hermitian and unitary matrices.
Matrices are made permanent with the possibility of using even after one year.
I might get something wrong about hermitian random matrices.
Fundamental and essential matrices, their robust estimation, camera calibration.
Interlaminar fracture toughness of composites with different matrices 2015.
In later years she adjusted some of the matrices to fit expressive artistic frames.
I have reconfigured the data core but it still won't support our matrices.
Different types of generalized inverse matrices- computation algorithms and their applications.
I have been able to reconfigure the data core, but it's still not capable of supporting our matrices.
All I need to do is vyq'tal the qen'dioqe matrices, stabilize the per'cheya, tez'tel se nenna.
Bituminisation extruder to compare fixation of liquid radioactive waste to different types of bitumen matrices.
Linear Algebra: Matrices, operations with matrices, determinants, inverse matrices, eigenvalues.
Linear dependence and independence of vectors,base of a vector space, matrices, basic operations with matrices. .
As input matrices, images were used, which makes it possible to get a visual impression of the NMF approximation quality.
Development of methods for evaluation and rapid detection of selected lactic acid bacteria andbifidobacteria in complex matrices.
Student knows how to use operations with matrices and determinants for solving of systems of linear and matrix equations.
The main focus is on the related notions of linear spaces and linear transformations(linear independence,bases and coordinates) and matrices.
The popularity of BEM suffers from the fact that it is difficult to implement andthat the resulting system matrices are densely populated, thus, more computationally demanding.
In an effort to meet the demands of all those interested in organizing exhibitions, all works from the estate have been placed on loan,including the print matrices.
Local stiffness matrices can be efficiently regularized by standard Cholesky decomposition algorithm for regular matrices.