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Autores principales: Kordalis, L., Trevezas, S.
Formato: Preprint
Publicado: 2026
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Acceso en línea:https://arxiv.org/abs/2605.30379
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author Kordalis, L.
Trevezas, S.
author_facet Kordalis, L.
Trevezas, S.
contents We study the convolution product of matrix-valued sequences and its role in the computation of Markov renewal equations. Explicit representations and recursive formulae for the convolutional inverse are derived and used to construct FFT-accelerated convolution and Newton-type inversion schemes, together with a Gauss--Jordan alternative in truncated power-series rings. The proposed framework is also applied to discrete approximations of matrix Stieltjes convolutions, which arise in continuous-time semi-Markov models. These tools are then used for the numerical evaluation of semi-Markov reliability and availability functions. The numerical results show substantial reductions in runtime, while preserving close agreement with exact benchmark solutions, direct computations, and Monte Carlo simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2605_30379
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Algebraic and FFT-Based Methods for Discrete-Time Matrix Convolutions with Applications to Semi-Markov Models
Kordalis, L.
Trevezas, S.
Numerical Analysis
Probability
We study the convolution product of matrix-valued sequences and its role in the computation of Markov renewal equations. Explicit representations and recursive formulae for the convolutional inverse are derived and used to construct FFT-accelerated convolution and Newton-type inversion schemes, together with a Gauss--Jordan alternative in truncated power-series rings. The proposed framework is also applied to discrete approximations of matrix Stieltjes convolutions, which arise in continuous-time semi-Markov models. These tools are then used for the numerical evaluation of semi-Markov reliability and availability functions. The numerical results show substantial reductions in runtime, while preserving close agreement with exact benchmark solutions, direct computations, and Monte Carlo simulations.
title Algebraic and FFT-Based Methods for Discrete-Time Matrix Convolutions with Applications to Semi-Markov Models
topic Numerical Analysis
Probability
url https://arxiv.org/abs/2605.30379