Structured low-rank approximation (SLRA) is a mathematical framework that seeks to approximate a given data matrix by another matrix of lower rank while preserving intrinsic structural properties.

Future events such as the weather or satellite trajectories are computed in tiny time steps, so the computation must be both ...

This is a preview. Log in through your library . Abstract The paper is concerned with the characterization and computation of local best rational Chebyshev approximations to continuous complex-valued ...

Matrix functions, such as the exponential, square root and cosine, play an indispensable role in various fields including quantum mechanics, control theory and numerical solution of differential ...

This is a preview. Log in through your library . Abstract Spectral approximations on the triangle by orthogonal polynomials are studied in this paper. Optimal error ...

There’s a general consensus that we won’t be able to consistently perform sophisticated quantum calculations without the development of error-corrected quantum computing, which is unlikely to arrive ...

It is here assumed that errors in any one link of a distribution chain are distributed rectangularly, and that each such distribution can be regarded as discrete or quantized. It is also assumed that ...