@inproceedings{983e360b40f04d839fc5e92bf2274295,
title = "Complexity of Alpha-Beta bidirectional associative memories",
abstract = "Most models of Bidirectional Associative Memories intend to achieve that all trained patterns correspond to stable states; however, this has not been possible. Also, none of the former models has been able to recall all the trained patterns. A new model which appeared recently, called Alpha-Beta Bidirectional Associative Memory (BAM), recalls 100% of the trained patterns, without error. Also, the model is non iterative and has no stability problems. In this work the analysis of time and space complexity of the Alpha-Beta BAM is presented.",
keywords = "Alpha-Beta associative memories, Bidirectional associative memories, Complexity, Perfect recall",
author = "Acevedo-Mosqueda, {Mar{\'i}a Elena} and Cornelio Y{\'a}{\~n}ez-M{\'a}rquez and Itzam{\'a} L{\'o}pez-Y{\'a}{\~n}ez",
year = "2006",
doi = "10.1007/11925231_34",
language = "Ingl{\'e}s",
isbn = "3540490264",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "357--366",
booktitle = "MICAI 2006",
address = "Alemania",
note = "5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence ; Conference date: 13-11-2006 Through 17-11-2006",
}