Abstract
In this paper various methods of CNAM learning (synthesis) are compared in order to find their common features. This allows to transfer the important characteristics among the methods, and to do some assumptions about their capabilities. Also the influence of learning parameters in some methods on the CNAM stability is investigated, and recommendations on their choice are given.
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© 1999 Springer-Verlag Berlin Heidelberg
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Pudov, S. (1999). Comparative Analysis of Learning Methods of Cellular-Neural Associative Memory. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 1999. Lecture Notes in Computer Science, vol 1662. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48387-X_12
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DOI: https://doi.org/10.1007/3-540-48387-X_12
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