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arXiv · 2306.00135

Optimal Approximate Minimization of One-Letter Weighted Finite Automata

Clara Lacroce·Borja Balle·Prakash Panangaden·Guillaume Rabusseau
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Abstract

In this paper, we study the approximate minimization problem of weighted finite automata (WFAs): to compute the best possible approximation of a WFA given a bound on the number of states. By reformulating the problem in terms of Hankel matrices, we leverage classical results on the approximation of Hankel operators, namely the celebrated Adamyan-Arov-Krein (AAK) theory. We solve the optimal spectral-norm approximate minimization problem for irredundant WFAs with real weights, defined over a one-letter alphabet. We present a theoretical analysis based on AAK theory, and bounds on the quality of the approximation in the spectral norm and $\ell^2$ norm. Moreover, we provide a closed-form solution, and an algorithm, to compute the optimal approximation of a given size in polynomial time.

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Clara Lacroce, Borja Balle, Prakash Panangaden, Guillaume Rabusseau. 2023-05-31. Optimal Approximate Minimization of One-Letter Weighted Finite Automata. https://doi.org/10.1017/s0960129524000276

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