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.

The evaluation of mathematical functions in hardware is a critical aspect of modern digital system design, particularly in domains such as image analysis, signal processing and embedded computing.

Kövari and Pommerenke [19], and Elliott [8], have shown that the truncated Faber series gives a polynomial approximation which (for practical values of the degree of the polynomial) is very close to ...

Abstract: Ensuring reliability in modern computing systems requires efficient and accurate error detection mechanisms. This paper explores a machine learning based ...

1 Warwick Mathematics Institute, The University of Warwick, Coventry, United Kingdom 2 School of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang, China To ...

This is a preview. Log in through your library . Abstract We study the approximation properties of some general finite-element spaces constructed using improved graded meshes. In our results, either ...

I would like to get an accurate estimate of the latent correlation matrix. There is no compiling error, but I've observed that when I use both the original and approx, I reach a maximum iteration ...

That frequency generates a lot of data to parse through and a powerful decoding process to get the required answer. This is a ...