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<Paper uid="C92-1021">
  <Title>Hopfield Models as Nondeterministic Finite-State Machines</Title>
  <Section position="9" start_page="0" end_page="0" type="concl">
    <SectionTitle>
8 Conclusions
</SectionTitle>
    <Paragraph position="0"> We proposed an receptor for all context-free languages with limited center-embedding, and a suitable variant of the Ilopfield mode\]. The formal model was implemented on the lloptield model, and a correct= uess theorem for the latter was given. Simulation restilts provided initial corroboration ofonr theory. The obtamed neural-network receptor is fast but large.</Paragraph>
    <Paragraph position="1"> Continuation of this research in the near fnture consists of the design of an adaptive variant of this mode\[, one that learns a grammar from examples in an unsupervised fashion.</Paragraph>
  </Section>
class="xml-element"></Paper>