Learning and Extracting Initial Mealy Automata with a Modular Neural Network Model

@article{Tio1995LearningAE,
  title={Learning and Extracting Initial Mealy Automata with a Modular Neural Network Model},
  author={Peter Tio and Jozef ajda},
  journal={Neural Computation},
  year={1995},
  volume={7},
  pages={822-844}
}
A hybrid recurrent neural network is shown to learn small initial mealy machines (that can be thought of as translation machines translating input strings to corresponding output strings, as opposed to recognition automata that classify strings as either grammatical or nongrammatical) from positive training samples. A well-trained neural net is then presented once again with the training set and a Kohonen self-organizing map with the star topology of neurons is used to quantize recurrent… CONTINUE READING

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References

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Showing 1-10 of 26 references

Learning finite state transducers with a recurrent neural network

  • D. Chen, C. L. Giles, G. Z. Sun, H. H. Chen, Y. C. Lee
  • IJCNN Int. Conf. Neural Networks, Beijing, China…
  • 1992
Highly Influential
4 Excerpts

Induction of discrete-state machine by stabilizing a simple recurrent network using clustering

  • S. Das, R. Das
  • Comput . Sci . Informatics
  • 1991
Highly Influential
7 Excerpts

Inserting rules into recurrent neural network

  • C. L. Giles, C. W. Omlin
  • Proc. 1992 I E E E Workshop Neural Networks…
  • 1992
Highly Influential
2 Excerpts

A n Introduction to Automata Theory

  • M. W. Shields
  • Blackwell Scientific Publications, London.
  • 1987
Highly Influential
3 Excerpts

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