Hyper-Minimization for Deterministic Weighted Tree Automata
Formal Languages and Automata Theory
2014-05-23 v1 Computational Complexity
Data Structures and Algorithms
Abstract
Hyper-minimization is a state reduction technique that allows a finite change in the semantics. The theory for hyper-minimization of deterministic weighted tree automata is provided. The presence of weights slightly complicates the situation in comparison to the unweighted case. In addition, the first hyper-minimization algorithm for deterministic weighted tree automata, weighted over commutative semifields, is provided together with some implementation remarks that enable an efficient implementation. In fact, the same run-time O(m log n) as in the unweighted case is obtained, where m is the size of the deterministic weighted tree automaton and n is its number of states.
Keywords
Cite
@article{arxiv.1405.5610,
title = {Hyper-Minimization for Deterministic Weighted Tree Automata},
author = {Andreas Maletti and Daniel Quernheim},
journal= {arXiv preprint arXiv:1405.5610},
year = {2014}
}
Comments
In Proceedings AFL 2014, arXiv:1405.5272