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.

• Type: Conference
• Year: 2000
• Where: SSPR
• Authors: Mikel L. Forcada, Rafael C. Carrasco
• Keywords: Finitestate Tree Automata, Important Language-theoretical Formalizations, Pattern Recognition, Recursive Neural Nets, SSPR 2000