Abstract
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.
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Shirotori, T., Osana, Y. (2009). Improved Kohonen Feature Map Associative Memory with Area Representation for Sequential Analog Patterns. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5768. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04274-4_53
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DOI: https://doi.org/10.1007/978-3-642-04274-4_53
Publisher Name: Springer, Berlin, Heidelberg
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