Abstract
The Lernmatrix, which is the first known model of associative memory, is a hetereoassociative memory that presents the problem of incorrect pattern recall, even in the fundamental set, depending on the associations. In this work we propose a new algorithm and the corresponding theoretical support to improve the recalling capacity of the original model.
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Román-Godínez, I., López-Yáñez, I., Yáñez-Márquez, C. (2007). Perfect Recall on the Lernmatrix. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_100
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DOI: https://doi.org/10.1007/978-3-540-72393-6_100
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72392-9
Online ISBN: 978-3-540-72393-6
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