An Attractor Neural Network Model of Recall and Recognition
Abstract
This work presents an Attractor Neural Network (ANN) model of Re(cid:173) call and Recognition. It is shown that an ANN model can qualitatively account for a wide range of experimental psychological data pertaining to the these two main aspects of memory access. Certain psychological phenomena are accounted for, including the effects of list-length, word(cid:173) frequency, presentation time, context shift, and aging. Thereafter, the probabilities of successful Recall and Recognition are estimated, in order to possibly enable further quantitative examination of the model.
Cite
Text
Ruppin and Yeshurun. "An Attractor Neural Network Model of Recall and Recognition." Neural Information Processing Systems, 1990.Markdown
[Ruppin and Yeshurun. "An Attractor Neural Network Model of Recall and Recognition." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/ruppin1990neurips-attractor/)BibTeX
@inproceedings{ruppin1990neurips-attractor,
title = {{An Attractor Neural Network Model of Recall and Recognition}},
author = {Ruppin, Eytan and Yeshurun, Yehezkel},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {642-648},
url = {https://mlanthology.org/neurips/1990/ruppin1990neurips-attractor/}
}