Recursive hetero-associative memories for translation

  • Mikel L. Forcada
  • Ramón P. Ñeco
Plasticity Phenomena (Maturing, Learning and Memory)
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1240)


This paper presents a modification of Pollack's RAAM (Recursive Auto-Associative Memory), called a Recursive Hetero-Associative Memory (RHAM), and shows that it is capable of learning simple translation tasks, by building a state-Space representation of each input string and unfolding it to obtain the corresponding output string. RHAM-based translators are computationally more powerful and easier to train than their corresponding double-RAAM counterparts in the literature.


Hide Neuron Recurrent Neural Network Hide Unit Input String Empty String 
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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Mikel L. Forcada
    • 1
  • Ramón P. Ñeco
    • 1
  1. 1.Departament de Llenguatges i Sistemes InformàticsUniversitat d'AlacantAlacantSpain

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