An effective associative memory for pattern recognition

Authors

Boris Kryzhanovsky, Russian Academy of Sciences
Leonid Litinskii, Russian Academy of Sciences
Anatoly Fonarev, Kean University

Document Type

Article

Publication Date

1-1-2003

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.

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

First Page Number

179

Last Page Number

186

DOI

10.1007/978-3-540-45231-7_17

Recommended Citation

Kryzhanovsky, Boris; Litinskii, Leonid; and Fonarev, Anatoly, "An effective associative memory for pattern recognition" (2003). Kean Publications. 2705.
https://digitalcommons.kean.edu/keanpublications/2705