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An adaptive filter model for recognition memory
Author(s) -
Heath Richard A.,
Fulham Ross
Publication year - 1988
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1988.tb00891.x
Subject(s) - novelty , computer science , content addressable memory , associative property , artificial intelligence , stimulus (psychology) , filter (signal processing) , recognition memory , pattern recognition (psychology) , algorithm , speech recognition , artificial neural network , cognitive psychology , psychology , mathematics , computer vision , cognition , neuroscience , social psychology , pure mathematics
A model for the adaptive formation of an associative memory structure based on a stochastic approximation algorithm is described. This model incorporates a feedback loop which allows the modification to memory to depend upon the novelty of the stimulus input. Predictions are derived for change in the memory structure across trials and these results are applied to the analysis of serial position effects in the Sternberg item‐recognition paradigm as well as familiarity judgements in a continuous recognition task. Illustrative applications of the model arc presented.