Comparison of deterministic and fuzzy finite automata extraction methods from Jordan networks

@article{Simon2005ComparisonOD,
  title={Comparison of deterministic and fuzzy finite automata extraction methods from Jordan networks},
  author={Denise Regina Pechmann Simon and Adelmo Luis Cechin},
  journal={Fifth International Conference on Hybrid Intelligent Systems (HIS'05)},
  year={2005},
  pages={6 pp.-}
}
This paper compares two methods for the extraction of finite state automata from recurrent neural networks (RNNs). Neural networks store the knowledge implicit in the data in their weights, but do not provide an easy explanation of this knowledge to the user. This is a difficult task due to the spatial (distributed information in the network) and temporal (network states) relations built by the network among the data. One form to present the knowledge stored inside a RNN is using finite state… CONTINUE READING