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Rafael C. Carrasco, Mikel L. Forcada, "Simple Strategies to Encode Tree Automata in Sigmoid Recursive Neural Networks," IEEE Transactions on Knowledge and Data Engineering, vol. 13, no. 2, pp. 148156, March/April, 2001.  
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@article{ 10.1109/69.917555, author = {Rafael C. Carrasco and Mikel L. Forcada}, title = {Simple Strategies to Encode Tree Automata in Sigmoid Recursive Neural Networks}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {13}, number = {2}, issn = {10414347}, year = {2001}, pages = {148156}, doi = {http://doi.ieeecomputersociety.org/10.1109/69.917555}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Knowledge and Data Engineering TI  Simple Strategies to Encode Tree Automata in Sigmoid Recursive Neural Networks IS  2 SN  10414347 SP148 EP156 EPD  148156 A1  Rafael C. Carrasco, A1  Mikel L. Forcada, PY  2001 KW  Tree automata KW  recursive neural networks KW  neural computation KW  analog neural networks. VL  13 JA  IEEE Transactions on Knowledge and Data Engineering ER   
Abstract—Recently, a number of authors have explored the use of recursive neural nets (RNN) for the adaptive processing of trees or treelike structures. One of the most important languagetheoretical formalizations of the processing of treestructured data is that of deterministic finitestate tree automata (DFSTA). DFSTA may easily be realized as RNN using discretestate units, such as the threshold linear unit. A recent result by Síima (
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