Abstract
Neuron models of associative memory provide a new and prospective technology for reliable date storage and patterns recognition. However, even when the patterns are uncorrelated, the efficiency of most known models of associative memory is low. We developed a new version of associative memory with record characteristics of its storage capacity and noise immunity, which, in addition, is effective when recognizing correlated patterns. © Springer-Verlag Berlin Heidelberg 2003.
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CITATION STYLE
Kryzhanovsky, B., Litinskii, L., & Fonarev, A. (2003). An effective associative memory for pattern recognition. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2810, 179–186. https://doi.org/10.1007/978-3-540-45231-7_17
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