In this paper, we propose an improved Kohonen feature map associative memory with area representation for sequential analog patterns. This model is based on the conventional Kohonen feature map associative memory with area representation for sequential analog patterns. The proposed model has enough robustness for noisy input and damaged neurons. Moreover, the learning speed of the proposed model is faster than that of the conventional model. We carried out a series of computer experiments and confirmed the effectiveness of the proposed model. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Shirotori, T., & Osana, Y. (2009). Improved kohonen feature map associative memory with area representation for sequential analog patterns. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5768 LNCS, pp. 505–514). https://doi.org/10.1007/978-3-642-04274-4_53
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