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2000
Springer

Encoding Nondeterministic Finite-State Tree Automata in Sigmoid Recursive Neural Networks

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Encoding Nondeterministic Finite-State Tree Automata in Sigmoid Recursive Neural Networks
Abstract. Recently, a number of authors have explored the use of recursive recursive neural nets (RNN) for the adaptive processing of trees or tree-like structures. One of the most important language-theoretical formalizations of the processing of tree-structured data is that of finitestate tree automata (FSTA). In many cases, the number of states of a nondeterministic FSTA (NFSTA) recognizing a tree language may be smaller than that of the corresponding deterministic FSTA (DFSTA) (for example, the language of binary trees in which the label of the leftmost k-th order grandchild of the root node is the same as that on the leftmost leaf). This paper describes a scheme that directly encodes NFSTA in sigmoid RNN.
Mikel L. Forcada, Rafael C. Carrasco
Added 25 Aug 2010
Updated 25 Aug 2010
Type Conference
Year 2000
Where SSPR
Authors Mikel L. Forcada, Rafael C. Carrasco
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