Exemplos de uso de Numerical linear em Inglês e suas traduções para o Português
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Numerical linear algebra performance enhancements.
Additional documentation for low-level numerical linear algebra.
In numerical linear algebra, a Givens rotation is a rotation in the plane spanned by two coordinates axes.
Record-breaking speed through processor-optimized numerical linear algebra.
The main use of Givens rotations in numerical linear algebra is to introduce zeros in vectors or matrices.
His mother, Vera Faddeeva,was known for her work in numerical linear algebra.
Householder transformations are widely used in numerical linear algebra, to perform QR decompositions and is the first step of the QR algorithm.
The Frobenius norm is sub-multiplicative andis very useful for numerical linear algebra.
Numerical linear algebra is the study of algorithms for performing linear algebra computations, most notably matrix operations, on computers.
He is known for his contributions to parallel algorithms in numerical linear algebra.
Common problems in numerical linear algebra include computing the following: LU decomposition, QR decomposition, singular value decomposition, eigenvalues.
In 2008 he was awarded the Fröhlich Prize in recognition of'his leading contributions to numerical linear algebra and numerical stability analysis.
In numerical linear algebra, the Jacobi eigenvalue algorithm is an iterative method for the calculation of the eigenvalues and eigenvectors of a real symmetric matrix a process known as diagonalization.
He worked on the numerical solution of partial differential equations at a time when numerical linear algebra was performed on a desk calculator.
In numerical linear algebra the singular values can be used to determine the"effective rank" of a matrix, as rounding error may lead to small but non-zero singular values in a rank deficient matrix.
His 1951 paper The principle of minimized iterations in the solution of the eigenvalue problem is one of the most cited papers in numerical linear algebra.
They are determined by the department to provide a foundation for further study and cover numerical linear algebra, stochastic processes, boundary value problems, and combinatorics.
The method of least squares leads to a consideration of problems in an inner product space, involving projection onto subspaces, andthus the problem of minimizing the squared errors can be reduced to a problem in numerical linear algebra.
Therefore, in this study,the following models are developed: a numerical linear model of civil transport aircraft, which represents the longitudinal dynamics at the landing approach condition.
Polar decomposition Eigenvalue decomposition Spectral decomposition LU decomposition Singular value decomposition L. N. Trefethen andD. Bau, Numerical Linear Algebra SIAM, 1997.
Computational algorithms for finding the solutions are an important part of numerical linear algebra, and play a prominent role in engineering, physics, chemistry, computer science, and economics.
That gives us u1 up to uK which gives us the K direction onto which we want to project the data.the rest of the procedure from this SVD numerical linear algebra routine we get this matrix u.
So, just to wrap up the description of the rest of the procedure,from the SVD numerical linear algebra routine we get these matrices u, s, and d. we're going to use the first K columns of this matrix to get u1-uK.
Computer Geometry deepens theoretical knowledge in various algebraic and geometric subjects together with their applications in the geometry of computer vision and robotics, computer graphics and image processing,optimization methods, and numerical linear algebra.
Demmel is known for his work on LAPACK,a software library for numerical linear algebra and more generally for research in numerical algorithms combining mathematical rigor with high performance implementation.
In this paper we study regularization methods for total least squares problems(rtls)based on numerical linear algebra tools and regularization theory.
Algebraic equation sets that arise in the steady state problems are solved using numerical linear algebra methods, while ordinary differential equation sets that arise in the transient problems are solved by numerical integration using standard techniques such as Euler's method or the Runge-Kutta method.
In numerical linear algebra, a Jacobi rotation is a rotation," Q"" k" ℓ, of a 2-dimensional linear subspace of an" n-" dimensional inner product space, chosen to zero a symmetric pair of off-diagonal entries of an" n"×" n" real symmetric matrix," A", when applied as a similarity transformation:: formula 1: formula 2It is the core operation in the Jacobi eigenvalue algorithm, which is numerically stable and well-suited to implementation on parallel processors.
And if you're implementing this in a different language than Octave orMATLAB, what you should do is find the numerical linear algebra library that can compute the SVD or singular value decomposition, and there are many such libraries for probably all of the major programming languages.
A subjective psychometric response scale used to measure distinct behavioral orphysiological phenomena based on linear numerical gradient or yes/no alternatives.