英文互译镜像站

NFA minimization

Last updated

In automata theory (a branch of theoretical computer science), NFA minimization is the task of transforming a given nondeterministic finite automaton (NFA) into an equivalent NFA that has a minimum number of states, transitions, or both. While efficient algorithms exist for DFA minimization, NFA minimization is PSPACE-complete. [1] No efficient (polynomial time) algorithms are known, and under the standard assumption P ≠ PSPACE, none exist. The most efficient known algorithm is the Kameda‒Weiner algorithm. [2]

Contents

Non-uniqueness of minimal NFA

Unlike deterministic finite automata, minimal NFAs may not be unique. There may be multiple NFAs of the same size which accept the same regular language, but for which there is no equivalent NFA or DFA with fewer states.[ example needed ]

References

  1. ↑ Jiang, Tao; Ravikumar, B. (1993), "Minimal NFA Problems are Hard" , SIAM Journal on Computing, 22 (6): 1117–1141, doi:10.1137/0222067
  2. ↑ Kameda, Tsunehiko; Weiner, Peter (August 1970). "On the State Minimization of Nondeterministic Finite Automata". IEEE Transactions on Computers . C-19 (7). IEEE: 617–627. doi:10.1109/T-C.1970.222994. S2CID   31188224 . Retrieved 2020-05-03.


Chatbot img.png

This article about natural language processing is a stub. You can help Wikipedia by expanding it.

This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.
开源整站镜像工具 主动推送镜像站群 镜像站群系统 百变TDK镜像 网站离线镜像