• Publications
  • Influence
Accuracy and stability of numerical algorithms
  • N. Higham
  • Computer Science, Mathematics
  • 1 March 1999
From the Publisher: What is the most accurate way to sum floating point numbers? What are the advantages of IEEE arithmetic? How accurate is Gaussian elimination and what were the key breakthroughsExpand
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Functions of matrices - theory and computation
TLDR
A thorough and elegant treatment of the theory of matrix functions and numerical methods for computing them, including an overview of applications, new and unpublished research results, and improved algorithms. Expand
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Computing the nearest correlation matrix—a problem from finance
Given a symmetric matrix what is the nearest correlation matrix, that is, the nearest symmetric positive semidefinite matrix with unit diagonal? This problem arises in the finance industry, where theExpand
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COMPUTING A NEAREST SYMMETRIC POSITIVE SEMIDEFINITE MATRIX
The nearest symmetric positive semidefinite matrix in the Frobenius norm to an arbitrary real matrix A is shown to be (B + H)/2, where H is the symmetric polar factor of B=(A + AT)/2. In the 2-norm aExpand
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Functions Of Matrices
Matrix functions are used in many areas of linear algebra and arise in numerous applications in science and engineering. The most common matrix function is the matrix inverse; it is not treatedExpand
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Computing the Action of the Matrix Exponential, with an Application to Exponential Integrators
TLDR
A new algorithm is developed for computing $e^{tA}B$, where $A$ is an $n\times n$ matrix and $B$ is a sequence of $n_0$ matrices, and the only input parameter is a backward error tolerance. Expand
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NLEVP: A Collection of Nonlinear Eigenvalue Problems
TLDR
We present a collection of 52 nonlinear eigenvalue problems in the form of a MATLAB toolbox. Expand
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The numerical stability of barycentric Lagrange interpolation
The Lagrange representation of the interpolating polynomial can be rewritten in two more computationally attractive forms: a modified Lagrange form and a barycentric form. We give an error analysisExpand
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The Scaling and Squaring Method for the Matrix Exponential Revisited
  • N. Higham
  • Computer Science, Mathematics
  • SIAM J. Matrix Anal. Appl.
  • 1 April 2005
TLDR
The scaling and squaring method is the most widely used method for computing the matrix exponential, not least because it is the method implemented in MATLAB's {\tt expm} function. Expand
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The Scaling and Squaring Method for the Matrix Exponential Revisited
TLDR
The scaling and squaring method is the most widely used method for computing the matrix exponential, not least because it is the method implemented in the MATLAB function expm. Expand
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