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Connectionist hashed associative memory

✍ Scribed by Ronald L. Greene

Publisher: Elsevier Science
Year: 1991
Tongue: English
Weight: 586 KB
Volume: 48
Category: Article
ISSN: 0004-3702
DOI: 10.1016/0004-3702(91)90081-t

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✦ Synopsis

Greene, R.L., Connectionist hashed associative memory (Research Note), Artificial Intelligence 48 (1991) 87-98. This paper proposes the use of simple connectionist networks as hashing functions for sparse associative or content addressable memory. The robustness of such networks in the presence of noisy inputs, and the property that "similar inputs lead to similar outputs" permits (in a probabilistic sense) faster-than-linear retrieval of data which best fits the input. The input may be noisy or have partially specified feature vectors. Mathematical analysis is presented for the Boolean feature case using a network with randomly selected connection strengths.

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